Podcasts about using big data

"Using Big Data and Causal Methods to Improve Clinical Practice" The Anne Klibanski Visiting Lecture Series was created to support and advance the careers of women. These lectures offer the opportunity for women faculty from outside institutions that have hosted Anne Klibanski Scholars to present on their expertise, either alone or in tandem with an Anne Klibanski Scholar. Presenter: Anthea Lindquist, MBBS, DPhil, Obstetrician/gynaecologist and perinatal epidemiologist, Mercy Hospital for Women, University of Melbourne, Australia Learning Objectives: Upon completion of this activity, participants were able to: Gain an understanding of the potential role of causal inference methods in clinical decision-making. Gain an appreciation of how big data and causal methods can help answer difficult clinical questions in obstetric practice. Review the current gaps in pharmacoepidemiology in obstetrics and how these methods might be able to fill these gaps. Click here to watch webinar.

To date, most autonomous vehicle testing has been conducted in urban areas, making it difficult to address the safety concerns of rural driving. But a joint effort between DriveOhio, TRC, and Youngstown State University is working to change that. The team is working to demonstrate how connected and automated vehicles could improve safety for drivers, passengers, and other travelers in rural settings. Join us to hear how they're harnessing big data to examine roadway safety, how their findings can be used to reduce fatalities, and what the future of AVs looks like in rural areas.Guests include Andrew Wallace of DriveOhio, Dr. Jay Kerns of YSU, and Dr. Punit Tulpule of TRC. They are joined by YSU graduate students Christoffer Splain, Vince Hepola, Christopher Bluhm, Felix Kina, and Emmanuel Asamanyuah, as well as undergraduate students Tyler Wood, Anthony Micco, and Nick Winsen.

Big data is reshaping industries and economies, and Real estate is ripe for disruption. In this wide-ranging conversation with Goose McGrath founder and CEO of Dashdot, you'll discover how data-based decisions are being used to inform savvy property investments that help people escape the status quo. This is good old property, but not at all as you know it.  Also in this episode:The 3 stages of financial freedomThe key insight behind Dashdot's unique approach Why property is not at all like the stock market How to think about and approach risk in investing and life Scientific investing and how it differs from traditional investingS curve dynamics in Real Estate The three phases of a property portfolio The three constraints of a property portfolio Property predictions for 2024/25Resources and Links Dashdot - Property Growth PartnerDashdot Insider - PodcastThe Wild Goose Chase - PodcastGoose McGrath - Linkedin Profile  Join the Private Podcast CommunityClick here to access free courses and trainings, build new habits, and connect with us and others on the journey to financial self reliance. Other links

Leah Boustan of Princeton University and Ran Abramitzky of Stanford University join the Essential Podcast to discuss their book “Streets of Gold: America's Untold Story of Immigrant Success”.

Crunch the Numbers: Using Big Data to Achieve Better Verdicts Too often, lawyers use guesswork to make decisions in cases worth tens of millions of dollars. And while gut feelings can be powerful, what if you could make decisions based on hard data instead? That's exactly what John Campbell is helping lawyers do every day. John has come up with an innovative method of using scientific survey techniques to predict outcomes of jury trials. His studies can tell you whether you're likely to win or lose a case, how much compensation you're likely to get from a jury, and even how you should structure your case to get the best verdict. John developed this technique during his tenure as a professor at the University of Denver Sturm College of Law, and to date, he's helped lawyers recover nearly $2 billion in trial. This week, John walks us through how his system works and the amazing results they've seen. Learn how your firm can start making better-informed decisions in trial, from jury selection to your closing argument. Key takeaways Big data can help you get better verdicts. John's system has proven to be incredibly accurate at predicting what a jury will award in a case. Not only can you make sure you're not asking so much that the jury will vote against you, but you can make sure you're not leaving any money on the table. The earlier you start studying the case, the more options you have. If you call John in two weeks before trial, he can perform a study, but you'll be limited in the changes you can make to get the best result. If you call him in early, he can help you shape your case to get the best possible outcome.  Creating empathy with the jury is key. Using techniques like “the man in the black suit” can help jurors start to put themselves in the plaintiff's shoes. This may make them more likely to return a larger settlement for your client. To contact John Campbell, visit his website (below) or text him at (314) 249-2500. Tip The Scales Podcast Tip the Scales Instagram Maria Monroy Instagram Maria Monroy LinkedIn LawRank Website LawRank Instagram LawRank Facebook LawRank LinkedIn LawRank Twitter Campbell Law, LLC Website Previous Guests: Bob Simon, Gary Sarner, Jen Gore-Cuthbert, Muhammad Ramadan, Amanda Baggett, Sara Williams, Joe Fried, Bibi Fell, Sahm Manouchehri, Sevy Fisher, Taly Goody, Teresa Diep, Dan Ambrose, Rick Ferri, Glen Lerner, and many others Other episodes you might enjoy: 6. Pick a Winning Jury: Make the Emotional Connection 20. Courage and Intention: How Radical Honesty Creates Stronger Attorneys 28. Study Connection: Learning from the Best to Improve Your Communication 36. Spotlight on EvenUp: Leveraging AI to Level the PI Playing Field 38. Keep Your Balance: Focusing on What Matters Most

Crunch the Numbers: Using Big Data to Achieve Better VerdictsToo often, lawyers use guesswork to make decisions in cases worth tens of millions of dollars. And while gut feelings can be powerful, what if you could make decisions based on hard data instead? That's exactly what John Campbell is helping lawyers do every day. John has come up with an innovative method of using scientific survey techniques to predict the outcomes of jury trials. His studies can tell you whether you're likely to win or lose a case, how much compensation you're likely to get from a jury, and even how you should structure your case to get the best verdict. John developed this technique during his tenure as a professor at the University of Denver Sturm College of Law, and to date, he's helped lawyers recover nearly $2 billion in trial. This week, John walks us through how his system works and the amazing results they've seen. Learn how your firm can start making better-informed decisions in trial, from jury selection to your closing argument. Key takeaways: Big data can help you get better verdicts. John's system has proven to be incredibly accurate at predicting what a jury will award in a case. Not only can you make sure you're not asking so much that the jury will vote against you, but you can make sure you're not leaving any money on the table. The earlier you start studying the case, the more options you have. If you call John in two weeks before trial, he can perform a study, but you'll be limited in the changes you can make to get the best result. If you call him in early, he can help you shape your case to get the best possible outcome.  Creating empathy with the jury is key. Using techniques like “the man in the black suit” can help jurors start to put themselves in the plaintiff's shoes. This may make them more likely to return a larger settlement for your client. To contact John Campbell, visit his website (below) or text him at (314) 249-2500. Tip The Scales Podcast Tip the Scales Instagram Maria Monroy Instagram Maria Monroy LinkedIn LawRank Website LawRank Instagram LawRank Facebook LawRank LinkedIn LawRank Twitter Campbell Law, LLC Website Previous Guests: Bob Simon, Gary Sarner, Jen Gore-Cuthbert, Muhammad Ramadan, Amanda Baggett, Sara Williams, Joe Fried, Bibi Fell, Sahm Manouchehri, Sevy Fisher, Taly Goody, Teresa Diep, Dan Ambrose, Rick Ferri, Glen Lerner, and many other episodes you might enjoy: 6. Pick a Winning Jury: Make the Emotional Connection 20. Courage and Intention: How Radical Honesty Creates Stronger Attorneys 28. Study Connection: Learning from the Best to Improve Your Communication 36. Spotlight on EvenUp: Leveraging AI to Level the PI Playing Field38. Keep Your Balance: Focusing on What Matters Most

This podcast is a commentary and does not contain any copyrighted material of the reference source. We strongly recommend accessing/buying the reference source at the same time. ■Reference Source https://www.ted.com/talks/ben_wellington_how_we_found_the_worst_place_to_park_in_new_york_city_using_big_data ■Post on this topic (You can get FREE learning materials!) https://englist.me/92-academic-words-reference-from-ben-wellington-how-we-found-the-worst-place-to-park-in-new-york-city-using-big-data-ted-talk/ ■Youtube Video https://youtu.be/9ZYaIAJLvFM (All Words) https://youtu.be/_gKS-VUY5YI (Advanced Words) https://youtu.be/rXzVCWlUYcM (Quick Look) ■Top Page for Further Materials https://englist.me/ ■SNS (Please follow!)

In this episode, we talk about transportation systems with Deb Heiser, Engineering Director of St. Louis Park, MN.  We discuss handling citizen requests,neighborhood meetings, how the city uses pilot projects to test traffic control changes in advance of street reconstruction projects, and her use of big data. Further Resourceshttps://www.streetlightdata.com/  http://www.mikeontraffic.com/temporary-traffic-calming-example/  

In our first ever live and in-person episode, we chat with Sandra Matz about the opportunities and challenges for using big data to understand human behavior Links Everybody lies book (https://www.amazon.com/Everybody-Lies-Internet-About-Really/dp/0062390856), by Seth Stephens-Davidowitz A paper (https://link.springer.com/article/10.3758/s13428-015-0630-z) on "Born open" data Other links Everything Hertz on social media - Dan on twitter (https://www.twitter.com/dsquintana) - James on twitter (https://www.twitter.com/jamesheathers) - Everything Hertz on twitter (https://www.twitter.com/hertzpodcast) - Everything Hertz on Facebook (https://www.facebook.com/everythinghertzpodcast/) Support us on Patreon (https://www.patreon.com/hertzpodcast) and get bonus stuff! $1 per month: A 20% discount on Everything Hertz merchandise, access to the occasional bonus episode, and the the warm feeling you're supporting the show $5 per month or more: All the stuff you get in the one dollar tier PLUS a bonus episode every month Citation Quintana, D.S., Heathers, J.A.J. (Hosts). (2023, May 31) "169: Using big data to understand behavior (Live episode with Sandra Matz)", Everything Hertz [Audio podcast], DOI: 10.17605/OSF.IO/JDXHF Special Guest: Sandra Matz.

On this week's episode of the Governance Podcast, Mark Pennington, the Director at the Study of Governance and Society here at King College London, interviews Professor Diane Coyle. This episode is titled "The data that is and that data the isn't: the pitfalls of using big data", and discusses the various uses and implications of big data in society, and the many pitfalls that may arise.  The Conversation ‘Big Data' fuels AI models like ChatGPT and the machine learning systems that are generating much debate about their promise – and peril – for decision-making. The impact of the technology will depend on the character of the data used. While the issue of data bias is well-understood (although not solved), less attention has been paid to other aspects such as data quality (is the data an accurate measure of the underlying object?), missing data (do we have only part of the picture?), and the meaning of data (how are the underlying concepts represented by the data constructed and interpreted)? As AI models are advancing fast enough to be deployed increasingly widely in society, there is a pressing need to reflect on the perspective on our social world created for them through the data on which they are trained and updated. The Guest Professor Diane Coyle is the Bennett Professor of Public Policy at the University of Cambridge. Diane co-directs the Bennett Institute where she heads research under the themes of progress and productivity. Her latest book is ‘Cogs and Monsters: What Economics Is, and What It Should Be‘ on how economics needs to change to keep pace with the twenty-first century and the digital economy. Diane is also a Director of the Productivity Institute, a Fellow of the Office for National Statistics, an expert adviser to the National Infrastructure Commission, and Senior Independent Member of the ESRC Council. She has served in public service roles including as Vice Chair of the BBC Trust, member of the Competition Commission, of the Migration Advisory Committee and of the Natural Capital Committee. Diane was Professor of Economics at the University of Manchester until March 2018 and was awarded a CBE for her contribution to the public understanding of economics in the 2018 New Year Honours.

Kenny Berger and guest attorney, professor, and researcher John Campbell of Campbell Law LLC discuss using big data jury studies to identify the strengths and weaknesses in your case, determine its true value, and understand what the jury is thinking so you can make decisions with confidence. 

Big data is present everywhere, irrespective of industry, domain, or function. It is now essential to make sense of big data and incorporate the insights into building the right content and engagement strategies. Some tactics that can be used to build the right way will be shared along with some case studies.Check out upcoming DigiMarCon Digital Marketing, Media, and Advertising Conferences & Exhibitions Worldwide at https://digimarcon.com/events/

Xi Jinping's Plan of Dominating the World Using Big Data and Artificial Intelligence

Dr. Quynh Nguyen is an assistant professor of epidemiology and biostatistics at the University of Maryland School of Public Health. She received her PhD and MSPH in Epidemiology from University of North Carolina at Chapel Hill, Gillings School of Global Public Health. Dr. Nguyen is a social epidemiologist focusing on contextual and economic factors as they relate to health. She joined us to talk about her projects that leverage technology and big data sources to investigate and address health disparities. Host: Raeesa Kabir Producer: Kirsi Oldenburg Artwork: Saurin Kantesaria Follow us on Twitter: @TheMaMLPodcast Have a speaker you would like to see on our podcast? Contact us at contact@themamlpodcast.com

ON THIS EPISODE: KAVANAUGH ASSASSINATION ATTEMPT The only feature of the tumult of the 1960s we haven't had is the assassinations. We are a people standing on shaky ground. We can't handle a major assassination. We can learn a lot from this plot and from whence it came. THE CHURCH AND BIG DATA Some churches are now using the same tactics that major digital media and digital advertisers use to target potential members or target people in need. Are you okay with churches using the same tactics as Google, Amazon, and other tech giants? WE HAVE A WEIRD TAKE ON AGE IN THE US As we've discussed raising the age on when someone can buy certain guns, it has occurred to me that we have an almost schizophrenic view of age. Alcohol, smoking, maybe guns, and other items are too sensitive for 18-years-olds. At the same time, we say 18-year-olds are mature enough to vote, take on large amounts of debt, or change their "gender." There is no cohesion. RAPID FIRE: -A way to fix social security -Funny but also crazy End Times "prophet" on YouTube -AOC misunderstands our government -Thoughts on the January 6th hearings --- Support this podcast: https://anchor.fm/corytruax/support

Right now, I reckon both ScoMo and Albo would do just about anything to have a crystal ball to show them Saturday's election results.  But such things don't exist. But, we do have the closest thing, and that's big data and artificial intelligence. And they're saying one thing loud and clear - people are fed up with the major parties and the leaders throwing insults at each other and are instead turning Teal. So much so, some analysts, like my next guest experienced economist and data strategist from maven Data, otherwise known as “The Data Whisperer”, Elisa Choy, are referring to this election as “Independents Day”.      See omnystudio.com/listener for privacy information.

Andrew Yeoman is the Chief Executive Officer & Co-Founder of Concirrus, an insurance software company based in London that provides a platform that empowers underwriters and brokers with insights and rating factors through AI. The platform works primarily by interpreting behavioral data from predictive models, which can outperform traditional risk assessment and underwriting techniques. Before co-founding Concirrus, Andrew held executive positions in various software companies, including Kudo Insurance. Andrew joins us to discuss how their platform provides more accurate insight into risks and utilizes behavioral data. He explains why behavior is the best indicator of risk, how climate change can affect it, and its various outcomes. He describes what led to the founding of Concirrus and the pain points they wish to address. Andrew also discusses the need for algorithms to help sort through important data and shares what's next in the pipeline for their company. "The fascinating thing about behavior is not only is it a better indicator of risk, it's a lead indicator of risk." - Andrew Yeoman Today on Spot On Insurance: Andrew's life as a child in West London, his passion for golf and entrepreneurship Why it was bad luck when Andrew wound up in insurance How their AI works with fleet behaviors to predict claims Why behavior is the best indicator of risk Rising natural disasters, climate change, and how it affects behaviors and outcomes Being overwhelmed with data and needing algorithms to help sort the important ones Andrew's ideal carrier and their pain points. What's next for Concirrus? Key Takeaways: 90% of the world's risks are uninsured right now. We live in an age where we're simply overwhelmed with data.

Links:Visit  Manolin's Website!Follow Manolin on Twitter!Check out our new website!: https://www.globalseafood.org/podcastFollow us on social media!Twitter | Facebook | LinkedIn | InstagramShare your sustainability tips with us podcast@globalseafood.org or leave us a voicemail at +1 (603) 384-3560!If you want to be more involved in the work that we do, become a member of the Global Seafood Alliance: https://www.globalseafood.org/membership/

Apple Podcasts Rate and Review for SpotOn Rao Tadepalli is the Founder & CEO of DigiTran, an InsurTech company that specializes in digital transformation. They help insurance companies innovate their legacy systems to digital and emerging technologies. Rao has over 30 years of experience working in insurance and has held executive positions since 1992. Rao also has extensive experience in core system transformation, property & casualty insurance, and computer science, among other skills. Rao joins us to discuss why legacy systems prevent digital transformation and explains how DigiTran helps insurance companies transition into digital systems and platforms. He shares his experience with working in various countries and what he's learned from all his travels. He describes the insurance industry in India and why it's still in its infancy. Rao also discusses the qualities an insurance leader needs to succeed in this industry. "Legacy systems are the biggest obstacle for digital transformation." - Rao Tadepalli Today on Spot On Insurance: Rao's childhood, growing up in India, and his fondness for computer science and engineering How Rao found a career in insurance Rao's travel experience and his thoughts on the various countries he's lived in The new developments we can expect to see in insurance What the FinTech and InsurTech industries are like in India Why insurance's profitability is measured differently compared to other major industries The qualities a leader should possess in insurance The problem with legacy systems and how it affects digital transformation How DigiTran helps carriers and the services they offer Key Takeaways: COVID-19 accelerated digital transformation. You cannot have digital transformation as long as you have ancient backend systems. Most people outside the insurance industry are disappointed at how long a sale can take. Connect with Rao Tadepalli: DigiTran DigiTran on LinkedIn Rao Tadepalli on LinkedIn Email: rao@digitran.ai This episode was brought to you by….. Insurance Licensing Services of America (ILSA), America's Premier Insurance Compliance and Licensing experts. To learn more about ILSA and their services, visit ILSAinc.com. Connect, Learn, Share Thank you for joining us on this week's episode of Spot On Insurance. For more resources and episodes, visit SpotOnInsurance.com. Subscribe so you never miss an episode. Love what you're learning, Spot Light your review on Apple Podcasts Rate and Review For SpotOn and share your favorite episodes with friends and colleagues!

A comprehensive new database designed to evalute everything from what Oklahomans are being charged with to who is taking plea deal and what kinds. In the moment, no one in Oklahoma has a comprehensive look at Oklahoma's criminal legal system or the prison and jail populations. Listen along with us today as we are joined by Ryan Kiesel to learn about HB 3848 and how data can cure some of Oklahoma's self inflicted wounds after decades of over-incarceration.

How does big data help make large public health decisions? How do we set up the collection, the analysis, and interoperate the data to create infrastructure? Leoson Hoay serves as a Research Analyst and Data Steward at the University of Chicago Urban Labs, working with the Health Lab team to support the creation of data-driven solutions to public health problems. Prior to joining the Urban Labs, he had worked in various fields spanning data engineering, mental health counseling, and environmental remediation with organizations in the US, Singapore, and Australia. Leoson received his MA in Computational Social Science from the University of Chicago, and his undergraduate degree in Psychology from the National University of Singapore. He is currently pursuing an MS in Computer Science at the Georgia Institute of Technology.In this episode we discuss many big questions invovling the use of big data to solve large problems. We dive into two projects Leoson has contributed to and generally discuss what big data means in the context of health decisions. Check it out! Leoson's Social Media: Linkedin Show Notes Tell us a little bit about what lead you to this path and what you do on a day to day basis?What does preventive medicine mean to you?How are large amounts of data able to be used to solve problems? What does the process look like? What are the challenges with this process?You have done research into the homeless population cycling between the streets, hospitals, and jails. Can you tell us about this project?Can you tell us a little bit more about your research with insurance backed psychiatric placement and providers?How do you measure the impact of these projects?What impact does the collection of data make on these projects and what changes were or could be made? How does data lead to infrastructure?Do you think that community social services can help prevent problems from occurring or are they most active at solving acute problems?Healthcare adds on a level of complexity for data collection with HIPPA and insurance companies. Are hospitals and insurance companies willing partners?What are some of the protective measures to safeguard privacy when working with healthcare data?If someone asks you how data contributes to health, what do you tell them? Join our Mailing List HERE: Mailchimp

Big data and some detective work helped Samkeek Roychowdhury, MD, PhD, and his team find a new target for immunotherapy. In this episode, Roychowdhury and Emily Hoskins, a graduate student in bioinformatics and a member of Roychowdhury's lab, fill us in on their research to discover a new target for immunotherapy and plans to create a clinical trial that shows great promise in treating patients with metastatic cancer.

  How To Find Wes Sheperd This is the company website hoodieanatlytics.com Email here wes at hoodieanalytics.com This is a production of Habanero Media. 

Rebecca Berbel talks with Jason Barnard about predictive SEO using big data. This is an extremely interesting and insightful episode where Rebecca Berbel and Jason Barnard discuss predictive SEO: where it came from, where it is now, and where it is going. Rebecca also cleared some misunderstandings between predicting in SEO and predictive SEO, ranking factors and features, and the explainable and unexplainable elements that contribute to the machine's predictions of ranking on the SERPs.  As always in SEO, there are loads and loads of “it depends”, so it doesn't look like predictive SEO will change that quirk in our industry :) Rebecca and Jason squeeze dozens of knowledge nuggets, tons of machine learning insights, and masses of SEO ranking analysis in this episode ;) Also, watch out for the answer to this pragmatic question: How can we present predictive SEO data to clients? What you'll learn from Rebecca Berbel 00:00 Rebecca Berbel with Jason Barnard 01:53 Rebecca Berbel's Brand SERP and her event Knowledge Panels 05:03 What is predicting in SEO and what is predictive SEO? 07:55 Contexts where “it depends” for ranking 09:51 Straight forward machine learning algorithms versus the black box 12:37 Thinking of factors as ML features 15:48 Why do you need to clean data? (garbage in, garbage out) 21:30 The three types of people in SEO  24:55 Explainability with Shapley (game theory) 29:20 Different sections of your site don't all behave the same way 33:01 Examples of negative SEO factors evaluated by OnCrawl's predictive model 36:36 Examples of positive SEO factors evaluated by OnCrawl's predictive model 38:30 How to win Google's game with data 40:33 How can we present predictive SEO to clients? 41:59 What output does predictive SEO provide? 44:11 The next steps in predictive SEO This episode was recorded live on video December 7th 2021 Recorded live at Kalicube Tuesdays (Digital Marketing Livestream Event Series). Watch the video now >>

Rebecca Berbel talks with Jason Barnard about predictive SEO using big data. This is an extremely interesting and insightful episode where Rebecca Berbel and Jason Barnard discuss predictive SEO: where it came from, where it is now, and where it is going. Rebecca also cleared some misunderstandings between predicting in SEO and predictive SEO, ranking factors and features, and the explainable and unexplainable elements that contribute to the machine's predictions of ranking on the SERPs.  As always in SEO, there are loads and loads of “it depends”, so it doesn't look like predictive SEO will change that quirk in our industry :) Rebecca and Jason squeeze dozens of knowledge nuggets, tons of machine learning insights, and masses of SEO ranking analysis in this episode ;) Also, watch out for the answer to this pragmatic question: How can we present predictive SEO data to clients? What you'll learn from Rebecca Berbel 00:00 Rebecca Berbel with Jason Barnard01:53 Rebecca Berbel's Brand SERP and her event Knowledge Panels05:03 What is predicting in SEO and what is predictive SEO?07:55 Contexts where “it depends” for ranking09:51 Straight forward machine learning algorithms versus the black box12:37 Thinking of factors as ML features15:48 Why do you need to clean data? (garbage in, garbage out)21:30 The three types of people in SEO 24:55 Explainability with Shapley (game theory)29:20 Different sections of your site don't all behave the same way33:01 Examples of negative SEO factors evaluated by OnCrawl's predictive model36:36 Examples of positive SEO factors evaluated by OnCrawl's predictive model38:30 How to win Google's game with data40:33 How can we present predictive SEO to clients?41:59 What output does predictive SEO provide?44:11 The next steps in predictive SEO This episode was recorded live on video December 7th 2021 Recorded live at Kalicube Tuesdays (Digital Marketing Livestream Event Series). Watch the video now >>

As a boy in Trinidad, he taught himself to program on an ancient Tandy TRS-80. He has a Master's in engineering and received his PhD in genomics while in medical school. My guest today is Dr. Dexter Hadley, the founding Chief of the Division of AI at the University of Central Florida's College of Medicine. Astronomically talented and a lover of rum, he's also a pioneering entrepreneur. As the founder of Hadley Lab, he strives to “translate big data into precision medicine and digital health.” In this episode, we'll dive into: How Dr. Hadley is optimizing AI for cancer research The immense conundrum of data privacy vs. medical advancement Recognizing and overcoming biases in your data How sharing your health data can help your community Training new doctors in the benefits of programming  Check out these resources we mentioned during the podcast: "From Bits to Bedside: Translating Big Data into Precision Medicine and Artificial Intelligence,” video by Dexter Hadley, M.D., Ph.D., UCF College of Medicine's Clinical and Computer Sciences “Translating Big Data Into Precision Screening and Diagnosis of Melanoma with Smartphones,” video by Dexter Hadley, M.D., Ph.D., UCF College of Medicine's Clinical and Computer Sciences  You can find this interview, and many more, by subscribing to In:Confidence podcast on Apple Podcasts, on Spotify, or here. Listening on a desktop & can't see the links? Just search for In:Confidence in your favorite podcast player.

The Global Fleet Voices video series produced by Automotive Fleet puts a spotlight on key leaders in today's fleet management industry. This episode is sponsored by and produced in partnership with Geotab

You may have heard me talk about leaning forward, and now a new term is hitting the journals Crisis Aware. What does that mean? Leaning forward can start with Big data. Using Big Data patterns to predict potential crises that can impact your organization, such as severe weather, pandemics, power outages not only is a beneficial practice within businesses, it can also improve the efficiency and effectiveness of emergency and disaster management organizations.With the use of smartphones, communication apps, and social media, disasters can be measured with real-time information and met with a rapid, accurate, and precise response. Big Data has the ability to enhance disaster recovery by utilizing community information and help you make the right decisions.The Business Continuity ShowTwitter - https://bit.ly/3ojEIO2Facebook - https://bit.ly/2Tjqv5HLinkedIn - https://bit.ly/34mXyfzYouTube - https://bit.ly/3mePJyGSister ShowsEM StudentWeb - https://bit.ly/2Hw0sFxTwitter - https://bit.ly/31z8MeXFacebook - https://bit.ly/3dMlbRPLinkedIn - https://bit.ly/34mXyfzYouTube - https://bit.ly/2FQDhWdEM WeeklyWebsite - https://bit.ly/3jj5ItlTwitter - https://bit.ly/31z8MeXFacebook - https://bit.ly/3dMlbRPLinkedIn - https://bit.ly/34mXyfzYouTube - https://bit.ly/2FQDhWdSee Less

In this episode Peter chats to John Barrington AM, Managing Director and Co-Founder at Artrya

We spend a lot of time thinking about and discussing trends in business and tech, so we're recording those thoughts. This weekend: Data is going to continue to impact every aspect of our lives, how can we use it correctly? Let us know what you think by emailing us at middletechpodcast@gmail.com or shooting us a DM on social! Twitter Instagram Facebook LinkedIn Visit us at MiddleTechPod.com

Food Security Portal Virtual Seminar Using Big Data and Machine Learning to Predict Poverty and Malnutrition for Targeting, Mapping, Monitoring, and Early Warning July 28, 2021, 08:00 am EDT Increasingly plentiful data and powerful predictive algorithms have heightened the promise of data science for humanitarian and development programming. As agencies increasingly embrace and invest in machine learning methods for poverty and malnutrition targeting, mapping, monitoring, and early warning, it is essential to recognize that different objectives require distinct data and methods. In this webinar, we highlight the differences between poverty and malnutrition targeting and mapping, the differences between structural and stochastic deprivation, and the modeling and data challenges of early warning systems development based on machine learning methods. We also present two studies that apply machine learning methods to predict poverty and malnutrition. This webinar is the second of a two-part webinar to present new data and findings from ongoing research under the United States Agency for International Development (USAID) (http://www.usaid.gov/)-funded project "Harnessing Big Data and Machine Learning to Feed the Future" (http://barrett.dyson.cornell.edu/research/innovations.html), based at Cornell University. Researchers and analysts from operational agencies are invited to join these events for a presentation and discussion of key principles, data sources, methods, and applications. Linden McBride, St Mary's College of Maryland, discussed a number of conceptual issues in this research area. Yanyan Liu, IFPRI, presented a study that uses publicly available, moderate-resolution vegetation index (normalized difference vegetation index, or NDVI) data and convolutional neural networks (CNNs) to produce accurate poverty estimates at the community level in low-income, rural economies. Chris Browne, Cornell University, presented a second study that demonstrates how interpretable multivariate random forest models can produce estimates of a set of (potentially correlated) malnutrition and poverty prevalence measures using free, open access, regularly updated, georeferenced data. Finally, Medha Bulumulla, Cornell University, briefly introduced the USAID project web site where data, papers, presentations, and code are freely available and walk participants through an annotated code that can be adapted and replicated for other applications. Presenters: Linden McBride (http://lindenmcbride.com/index.html), Assistant Professor, St Mary's College of Maryland, US Yanyan Liu (https://www.ifpri.org/profile/yanyan-liu), Senior Research Fellow, Markets, Trade and Institutions Division, IFPRI, USA Chris Browne (https://www.cam.cornell.edu/research/grad-students/chris-browne), PhD Candidate, Center for Applied Mathematics, Cornell University, USA Medha Bulumulla, Research Assistant, Cornell University, USA Moderator: Christopher B. Barrett (https://dyson.cornell.edu/faculty-research/faculty/cbb2/) , SB&JG Ashley Professor, Cornell University, USA Discussant: Rob Vos (https://www.ifpri.org/profile/rob-vos), Director of Markets, Trade and Institutions Division, IFPRI, USA For more information and other webinar materials, visit https://www.foodsecurityportal.org/node/1765 Other Food Security Portal (FSP) Events: https://www.foodsecurityportal.org/events

In this episode of Exploring Global Problems, Professor Ronan Lyons discusses with Dr Sam Blaxland how anonymised big data is used to help tackle all manner of health and well-being challenges and how this expertise informed Government Response to COVID-19. In a hard-hitting interview, Dr Blaxland explores what next? When can we expect to be back to normal? And were the sacrifices of peoples liberties and freedoms the right call? The work of Professor Ronan Lyons and his teams at Swansea University focus on using anonymised health data in order to help inform policy makers and practitioners across Wales, the UK and globally. Led by Professor Ronan Lyons, Professor in Public Health, Patient and Population Health Informatics researchers at Swansea University used their insight and expertise to help inform Welsh Government response to the COVID-19 pandemic. Their expertise actively helping respond and bring the pandemic under control in Wales.

Christine Boyle returns after 5 years and discusses her journey from 2015 start-up to 2018 sale. She provides hints and valuable insights for start-ups to make it through the “valley of death” and much more. Plus, Bluefield Research’s President, Reese Tisdale, joins us for another Bluefield on Tap segment talking about President Biden's infrastructure bill. In this session, you'll learn about: Christine's journey from start-up to sale to life inside a publicly traded company Why Christine made the decision to sell Valor Water to Xylem Practical advice for start-ups on how to build trust with clients Christine's take on how digital water has changed over the last 5 years Where Christine thinks digital water is going How small- and medium-size utilities can take advantage of digital water Christine's role in the technology incubator within Xylem Innovations Christine saw take off during the pandemic Christine's view of digital water and cybersecurity How innovation ecosystems in start-ups and big companies compare and contrast The issues on Christine's priority list for innovation going forward Resources and links mentioned in or relevant to this session include:  Christine's LinkedIn Page Xylem's website Xylem's One Minute in Water with Christine Boyle YouTube Video TWV #084: Using Big Data to Improve Water Utility Revenues with Valor Water President Christine Boyle TWV #170: Digitally Enabled Utility Resilience with Xylem's Albert Cho Thank You! Thanks to each of you for listening and spreading the word about The Water Values Podcast! Keep the emails coming and please rate and review The Water Values Podcast on iTunes and Stitcher if you haven't done so already. And don't forget to tell your friends about the podcast and whatever you do, don't forget to join The Water Values mailing list!

Christine Boyle returns after 5 years and discusses her journey from 2015 start-up to 2018 sale. She provides hints and valuable insights for start-ups to make it through the “valley of death” and much more. Plus, Bluefield Research’s President, Reese Tisdale, joins us for another Bluefield on Tap segment talking about President Biden’s infrastructure bill. In this session, you’ll learn about: Christine’s journey from start-up to sale to life inside a publicly traded company Why Christine made the decision to sell Valor Water to Xylem Practical advice for start-ups on how to build trust with clients Christine’s take on how digital water has changed over the last 5 years Where Christine thinks digital water is going How small- and medium-size utilities can take advantage of digital water Christine’s role in the technology incubator within Xylem Innovations Christine saw take off during the pandemic Christine’s view of digital water and cybersecurity How innovation ecosystems in start-ups and big companies compare and contrast The issues on Christine’s priority list for innovation going forward Resources and links mentioned in or relevant to this session include:  Christine’s LinkedIn Page Xylem’s website Xylem’s One Minute in Water with Christine Boyle YouTube Video TWV #084: Using Big Data to Improve Water Utility Revenues with Valor Water President Christine Boyle TWV #170: Digitally Enabled Utility Resilience with Xylem’s Albert Cho Thank You! Thanks to each of you for listening and spreading the word about The Water Values Podcast! Keep the emails coming and please rate and review The Water Values Podcast on iTunes and Stitcher if you haven’t done so already. And don’t forget to tell your friends about the podcast and whatever you do, don’t forget to join The Water Values mailing list!

We’ve stated many times that data is agnostic, a neutral tool that when used properly can be incredibly powerful in uncovering the truth of things. Or it can be used to obscure and manipulate the truth.  A recent study on Florida’s criminal justice system illustrates the point perfectly. Florida is known for being particularly tough on criminals. Because of this and other perceptions, researchers got curious about whether or not justice was being administered fairly in the sunshine state or if was distorted by racial or class based biases. Focusing on Jacksonville and Tampa (representing two very different parts of Florida) the study took into account things like plea deals, length of sentencing, prior records, and whether or not cases were even filed. Taking everything into account, it turns out that whatever perceptions may be, Florida is doing an excellent job in administering its justice fairly across the board. Florida’s justice may be tough, but it is fair.  The researchers also took a look at the same factors in places like Chicago and New York where they found major differences across racial lines. This is particularly interesting because based on stated policies, media coverage and other factors, many would expect the opposite answer.  What does this tell us about data and its importance? It tells us that whatever preconceptions we might have and how well founded we might think they are, it’s still possible for data to come and slap us around with the hard truth of reality. Naturally, this is uncomfortable, but it is exactly that discomfort that makes an honest and fair assessment of data so important. It is much better to proceed with an uncomfortable truth that might force us to reevaluate our own position than it is to carry on in blissful ignorance.  So what about the justice system in New York and Chicago? Are the judges and prosecutors there intentionally signaling out specific people? Probably not (though it would take further analysis to be sure), but after being presented with the data showing the racial disparities, they should also be willing to look at their own preconceptions to see if they need to face some uncomfortable truths on their end. As always, the truth is better than ignorance, even when it hurts. Data and an honest analysis of it can help us see where our blind spots are and point out the hard truths we need to confront.  Data can serve this function in many aspects of life. If someone wants to know whether a specific on and off ramp design would be an improvement, a civil engineer would have to find a similar example and crunch the numbers, checking for the amount of accidents, traffic jams, and other factors as compared with other designs. Or one could feed information about local traffic patterns into a computer model and run the simulation to get an idea of how well the design would work. Anyone who has had to deal with the cloverleaf design in rush hour wishes that modern data analysis and computer modeling was available when someone came up with that monstrosity.  Then there is the importance of data in medical science, especially now with the COVID virus still causing concern amongst many. How deadly is it? What treatments work? What measures work? All of these are important questions for understanding the virus and for making policy in how to deal with it. Unfortunately, too many decisions – such as eating in outdoor plastic bubbles – get made in the absence of data. All of this shows the true importance of data and how it can be used to evaluate and guide policy and action in the future. That’s why TARTLE places such an emphasis on data and getting it right from the source. When you’re getting it straight from the tap, the opportunities for manipulation and bias coming in are minimized, which means you are more likely to get the dose of cold hard truth we all need at times.  What’s your data worth? www.tartle.co  

On today's episode of our special series, 10 Days of Giving Back, we talk to Dr. Joan LaRovere, co-founder of Virtue Foundation, a groundbreaking nonprofit that provides actionable data and direct resources for communities most vulnerable to Covid-19 and other health crises. To learn how you can make a difference go to virtuefoundation.org. Learn more about your ad-choices at https://www.iheartpodcastnetwork.com

Dr. Matthew Churpek, Associate Professor of Medicine at the University of Wisconsin - Madison, presents on machine based learning and how it can be used in detection and early prevention of deteriorating patients.

Prior to her appointment as Associate Dean for Undergraduate Studies, Mary served as the Associate Chair and Director of Undergraduate Studies in the Economics Department. Her current research interests are economics pedagogy and the telecommunications industry. Dean Flannery received her B.A. and M.A in Economics from the University of Notre Dame in 1978 and 1979 respectively and her Ph.D. from the University of Maryland in 1996. Mary's faculty page Raj Chetty's “Using Big Data to Solve Economic and Social Problems Course” Vox's article on changing the way we teach undergrad economics Music sampled from Mos Def - Mathematics

Staffing has long been one of the Achilles heels of the nursing profession, confounding nurse managers and nurse leaders alike, and taking up an inordinate amount of time. Our guest for this episode is an expert on the topic and has taken her cues from other industries to treat this as a data science problem.  Early in her career, Therese Fitzpatrick was a chief nursing officer for various hospitals and health systems in the midwest before taking a turn as an entrepreneur, receiving her PhD in sociology and becoming a professor in the University of Illinois at Chicago's School of Public Health. Today she is an executive at consulting firm Kaufman Hall, where she helps hospitals across the country assess their clinical and operational performance, and optimize their staffing. In this episode Therese walks us through how she applies big data to the problems of staffing and workforce optimization, some low-tech ways that nurse managers can approach scheduling, and how COVID-19 will impact the evolution of the nursing workforce. Therese believes that robust float pools driven by Millenial and Gen Z nurses are the future and encourages nurse leaders to include them in conversations around staffing and workforce. Links to recommended reading:  Improving Quality of Nursing Worklife: A Global Perspective Using Labor Optimization for Nurse Staffing The Art and Science of Nurse Staffing (AACN) Effective Staffing Takes a Village: Creating the Staffing Ecosystem Advanced Analytics Must Drive the Next Round of Productivity Initiatives https://www.kaufmanhall.com/ The full transcript for this episode can be found here: www.trustedhealth.com/the-handoff-podcast/therese-fitzpatrick 

Albert Cho, Vice President and General Manager at Xylem, provides an insightful look at how digital technologies enhance the operational and financial resilience of utilities. Al discusses the benefits digitally enabled utilities have realized during the pandemic, provides examples of how utilities have gained financial efficiencies in the pre-pandemic deployment of capital and how those examples demonstrate that digital technologies play a significant role in helping utilities navigate the financial challenges ahead. In this session, you'll learn about: How digital technologies are performing during the COVID-19 pandemic How digital enhanced operational resilience in the early stage of response How utilities using digital technologies fared versus utilities using analog technologies How digital technologies impact utility financial resilience Why Al thinks the utility operational response in the first wave of the pandemic was miraculous (no massive failures, etc.) Why the biggest risk to utilities lies ahead in the form of financial impacts Why digital technologies can play a significant role in mitigating the financial impacts of the COVID-19 pandemic How Al distinguishes between “old smart water” and “new smart water” The tie between digital technologies and improved cash flow The significant savings realized by the City of South Bend, Indiana, by using digital technologies to optimize existing system assets Resources and links mentioned in or relevant to this session include: Albert's LinkedIn page Xylem's website Xylem's LinkedIn Page TWV #084: Using Big Data to Improve Water Utility Revenues with Valor Water President Christine Boyle Thank You! Thanks to each of you for listening and spreading the word about The Water Values Podcast! Keep the emails coming and please rate and review The Water Values Podcast on iTunes and Stitcher if you haven't done so already. And don't forget to tell your friends about the podcast and whatever you do, don't forget to join The Water Values mailing list!

Dr. Isaac Galatzer-Levy, Chief Scientific Officer at AiCure, talks about collecting data through cell phone platforms and building models to detect neurological symptoms for clinical trials.

More and more organisations are turning to big data to inform their decision-making, however they are finding that all is not well when they try to use big data. A new study by researcher Maryam Ghasemaghaei and Goran Calic from De Grot Business School at McMaster University looking at why organisations often end up abandoning the use of Big Data in their decision making, makes for some useful and interesting reading.  In this podcast I interview Dr. Maryam Ghasemaghaei about her research and findings. For the transcript and more go to: https://www.oxford-review.com/why-organisations-are-having-problems-using-big-data/

Our movements and habits are being tracks more and more with each passing year, and even sometimes days. All of that data can come in quite handy when you're looking to buy commercial real estate. Where are your customers coming from? Where are they going? How long do they spend in your location? This knowledge can be crucial when you're considering purchasing a property. Donna Salvatore is CEO and Founder of Megalytics, a company designed to take big data and decipher it for real estate investors, both big and small. Donna has worked with SaaS and IT companies for the past 22 years, and previously provided venture equity and debt financing for a decade. Key Takeaways: [2:28] Some areas of big data that commercial real estate investors that Megalytics can track [6:14] Has the retail apocalypse peaked yet? [10:18] What is the social media score and property management score that Megalytics provides? [15:29] The explosion in available data and what it looks like going forward [19:11] Big data isn't just for big commercial real estate investors, landlords of single family homes can use it as well Website: www.Megalytics.net

Wondering what you should do about “big data?" We sit down with Catalant expert Dave Herman to talk about two rising technologies that can drive deep insights into your business and give you a leg up on the competition. Dave shares how to get started with one of these technologies (data visualization) and the biggest mistake to avoid when trying to integrate it in your organization. He goes further into neural networks, sharing the story of how he became convinced of the power of such advanced analytics while working at a metal smelter in the Australian outback. Dave is advising leading industrial clients on these technologies and others and we're excited to share his insights in this episode. About Dave Herman: CEO at Anthros Consulting Former consultant at McKinsey & Company PhD, Materials Science & Engineering, Northwestern University BS, Materials Science & Engineering, Cornell University Interested in working with Dave? Visit www.gocatalant.com to get started. Episode highlights: 2:00 - Overview of data visualization and advanced analytics 3:30 - A firsthand story of seeing data visualization catapult a manager's career and spark organizational change 7:00 - How data visualization can reduce meeting time, drive insights, and result in decisions 7:45 - Advice for managers on getting up to speed on data visualization 9:15 - How NOT to incorporate data visualization into your company 11:15 - Dave's additional advice on how to get going with data visualization 13:30 - Neural networks as an advanced analytic technique and its power to drive insights 16:30 - The first steps a manager can take to get up to speed on neural networks or other advanced analytics 19:00 - The best advice Dave ever received and how managers can apply it Mentioned in this episode: Tableau Neural networks Microsoft BI Microsoft One Note Tableau For Dummies

If your company has diversity challenges look to data argues Iris Bohnet author of 'What Works.' See acast.com/privacy for privacy and opt-out information.

Christine Boyle, President of Valor Water, joins The Water Values Podcast to discuss how big data can make big improvements to utilities’ bottom lines and customer perceptions.

Today, we welcome the founder and CEO of miEdge.biz, Mark Smith, to ShapeShifters. The miEdge application is an affordable and easy to use service that combines an intuitive interface to a database and search engine of Department of Labor Health/Welfare Employee Benefits information. Get full show notes and more information here: http://bit.ly/1ran2RY

Katherine Milkman is an Assistant Professor at the Wharton School at the University of Pennsylvania. Her research relies heavily on "big data" to document various ways in which individuals systematically deviate from making optimal choices. Her work has paid particular attention to the question of what factors produce self-control failures (e.g., exercising too little or eating too much junk food) and how to reduce the incidence of such failures. Katherine has published in leading periodicals such as Management Science, the Proceedings of the National Academy of Sciences, and Psychological Science. She also is an Associate Editor for the Behavioral Economics Department at Management Science and a member of the Organizational Behavior and Human Decision Processes Editorial Board. Her work has been featured by media outlets such as The New York Times, The International Herald Tribune, BusinessWeek, The Economist, NPR, and Harvard Business Review. In 2011, Katherine was recognized as one of the top 40 business school professors under 40 by Poets and Quants, and in 2013 she was voted Wharton's "Iron Prof" by the school's MBA students. She graduated summa cum laude from Princeton University in Operations Research and Financial Engineering and has a Ph.D. from Harvard University's joint program in Computer Science and Business. In this interview, Katherine discusses her research in temptation bundling, planning props, and commitment devices among other topics and their implications to improving health behavior.

This week, Google Glass gets its first real review; will it alter the social contract? Turn any iPhone into a spycam, Groupon's CEO is fired, HP sells WebOS to LG, An Australian hacker knows the secrets of the next XBOX & Playstation, Is Reddit being gamed by marketers?, How NetFlix is using Big Data to turn us into their puppets, and How “Golden Eagle Snatches Kid” Ruled The Internet  Headlines I used Google Glass: the future, with monthly updates Sergey Brin: Smartphones are 'emasculating' Google Glass is a giant chisel to pry me out of Apple's ecosystem Is Google Glass Bad for Society? Koozoo turns any old iPhone into a 24/7 spycam Andrew Mason is out as CEO of Groupon, here's his sendoff letter HP emerges as big winner in webOS sale Audible Book of the Week Argo: How the CIA and Hollywood Pulled Off the Most Audacious Rescue in History by Antonio Mendez & Matt Baglio Sign up at AudibleTrial.com/TheDrillDown Musical Interlude: I Fought The Law by Green Day More Headlines The Incredible Rise and Fall of a Hacker Who Found the Secrets of the Next Xbox and PlayStation—And Maybe More Hail Corporate: The Increasingly Insufferable Fakery of Brands on Reddit For ‘House of Cards,' Using Big Data to Guarantee Its Popularity How Netflix is turning viewers into puppets Viral Video of the Week How “Golden Eagle Snatches Kid” Ruled The Internet Subscribe! The Drill Down on iTunes (Subscribe now!) Add us on Stitcher! The Drill Down on Facebook The Drill Down on Twitter Geeks Of Doom's The Drill Down is a roundtable-style audio podcast where we discuss the most important issues of the week, in tech and on the web and how they affect us all. Hosts are Geeks of Doom contributor Andrew Sorcini (Mr. BabyMan), VentureBeat editor Devindra Hardawar, marketing research analyst Dwayne De Freitas, and Startup Digest CTO Christopher Burnor. Occasionally joining them is Box tech consultant Tosin Onafowokan.