Dr. Shauna Overgaard is the Senior Director of AI Strategy & Frameworks at Mayo Clinic, where she focuses on applying AI and data science to healthcare. She also founded Clarity - Applied Intelligence and served as an Assistant Professor of Health Informatics and Information Management. She is active in several organizations like the Coalition for Health AI (CHAI) and the American Medical Informatics Association (AMIA), and is helping shape the future of AI in healthcare. With over 50 citations to her name, Dr. Overgaard has significantly contributed to AI model documentation, clinical decision support systems, and the ethical implementation of AI in healthcare. Our conversation took place in Fall 2024, and we’re starting to see how a lot of these predictions played out!
00:00 - Intro
04:05 - From rural Canada to a Senior Director at Mayo Clinic
06:30 - Innovation culture at Mayo
09:22 - It takes 17 years for AI to get to the clinic?!
15:58 - Giving patients ownership over their data
21:24 - Can paying patients for their data make ML models more equitable?
28:55 - Is bias inescapable with AI?
32:19 - Can we make AI more transparent without giving away intellectual property?
35:15 - Worries about AI replacing healthcare workers
36:52 - Silent Trials: beta-testing AI
39:25 - So uh, how’s Rochester?
42:00 - What gives your life meaning?
44:52 - Advice for navigating uncertain times and the AI revolution
Dr. Overgaard: linkedin.com/in/shaunaovergaard/
Host: Nathan Keller
Twitter: @NathanKellerX
Linkedin: linkedin.com/in/nathankeller1
Producer: Saurin Kantesaria & Garima Puri
LinkedIn: Saurin Kantesaria
Linkedin: linkedin.com/in/garimapuri/
Dr. Max Feinstein is a pediatric cardiac anesthesiologist and notably, a successful YouTuber. He has written on topics like AI’s role in future healthcare, vaping’s impact on anesthesiology, and recognizing burnout in medicine. Outside of the operating room, he somehow balances fellowship training, teaching, clinical work, and producing popular YouTube videos, demystifying anesthesia. Today we talk about his winding career path, vision for AI in the operating room, and the ethical implications of technology in modern medicine.
00:00 - Intro
1:16 - From majoring in philosophy to becoming an anesthesia resident
3:33 - Why medicine? Being a wilderness first responder
7:26 - Narrowing down a specialty - anesthesiology vs infectious disease
10:17 - What’s wrong with infectious disease?
11:46 - Why peds cardiac anesthesiology?
17:20 - Working and living in a soup kitchen in Colombia
22:29 - Who are all these people interested in anesthesia!?
27:00 - How Max makes videos
31:08 - We already have AI in anesthesia except…
46:56 - Future job market of anesthesia
50:36 - Consciousness and anesthesia
54:28 - Will AGI really help us?
56:53 - Ensuring patient safety in anesthesia
58:13 - Could AI make burnout worse?
1:02:36 - What gives your life meaning?
1:04:51 - Advice for Medical Students
YouTube - @MaxFeinsteinMD
Host: Nathan Keller
Twitter: @NathanKellerX
Linkedin: https://www.linkedin.com/in/nathankeller1/
Producer: Saurin Kantesaria
Linkedin: https://www.linkedin.com/in/saurin-kantesaria-0a464999
Dr. Steven Hart is a Senior Associate Consultant in AI at Mayo Clinic who has played a key role in shaping genomics and digital pathology with GenomeGPS, Mayo Clinic’s primary DNA sequencing workflow. His groundbreaking contributions have led to advancements in understanding inherited cancer risk and improving digital pathology workflows. With over 100 peer-reviewed publications, Dr. Hart’s innovative algorithms are driving efficiency in genetic predisposition testing, reducing unnecessary procedures, and enhancing precision healthcare.
We had some audio issues for this one which we tried to fix but they're still pretty apparent so apologies for that D:!
00:00:00 - Introduction
00:01:09 - From a factory worker to a leader in AI and medicine
00:05:11 - Proving people wrong as a motivator
00:06:37 - Crazy factory stories
00:07:38 - Why Mayo Clinic?
00:09:52 - Surprising things about Mayo Clinic
00:11:33 - Is Mayo Clinic’s data high quality?
00:12:55 - How to prepare healthcare for AI (and why AI won’t actually have the biggest impact)
00:20:50 - Democratizing pathology with AI
00:25:38 - Will AI replace pathologists?
00:29:24 - How do you judge how well an embedding works?
00:33:22 - Reducing expectations for diagnostic AI usage in healthcare
00:36:46 - How do you keep up with the rapidly evolving pace of AI?
00:38:31 - OpenAI o1 and prompt hacking
00:41:27 - Are we close to artificial general intelligence?
00:47:03 - How helpful are regulatory agencies like the FDA with translating AI?
00:49:52 - What makes a good question?
00:53:33 - Favorite parts about living in Rochester, MN
00:55:14 - What gives your life meaning?
00:58:36 - Advice for young people in uncertain times
Host: Nathan Keller
Twitter: @NathanKellerX
Linkedin: https://www.linkedin.com/in/nathankeller1/
Producer: Saurin Kantesaria
Linkedin: Saurin Kantesaria
Ran Shaul is the chief product officer and co-founder of K Health. With his robust background as a successful founder, Ran has been pivotal in transforming how we approach medical diagnostics and personalized treatment. Under his leadership, K Health has developed innovative AI-driven solutions, including a partnership with Cedars-Sinai and Mayo Clinic. Ran's dedication to improving the patient experience by leveraging technology is reshaping healthcare delivery, making it more efficient and accessible.
Host: Nathan Keller
Twitter: @NathanKellerX
Linkedin: https://www.linkedin.com/in/nathankeller1/
Producer: Saurin Kantesaria
Linkedin: Saurin Kantesaria
00:00 - Introduction
00:52 - What are 3 patient questions doctors and AI should help answer?
03:26 - Why does ChatGPT fall short in diagnosing patients?
07:30 - AI does the tedious stuff so doctors can focus on medicine (K Health’s model)
09:29 - Combing through 400,000,000 unstructured doctor’s notes
11:53 - How do you ask the right clinical questions with AI?
15:41 - Putting a clinician in the loop of AI learning
19:21 - “You can have the perfect algorithm…it does not mean it will be used properly in any clinical setting”
23:27 - The difficulties transitioning from leading a startup to a larger company
26:56 - Telemedicine 2.0 - integrating 24/7 online care with brick and mortar hospitals (Cedars-Sinai Virtual Platform)
31:32 - AI can go further than notes - helping physicians proactively manage patients
39:07 - What gives your life meaning?
42:56 - What advice do you have for young people?
Dr. Robert Dürichen leads the machine learning analytics team at Arcturis Data, a company focused on processing and analyzing large-scale electronic health record (EHR) datasets. His current research uses small and large language models to enrich EHR datasets from unstructured patient notes and improve quality through standardization techniques.
Hosts: Nathan Keller + Madeline Ahern
Twitter: @NathanKell57664 + @maddie_ahern
Audio/Video Editor + Art: Saurin Kantesaria
Linkedin: Saurin Kantesaria
Intro 0:00
Who is Robert Durichen? 1:29
What is Arcturis? 6:25
How can machine learning speed up clinical trials? 9:43
Typical Arcturis Project 12:06
Progression of Machine Learning 24:45
AI Taking Jobs 29:50
What is Arctex? 33:50
Who works at Arctex? 38:55
Future of Arcturis 40:58
What gives your life meaning? 43:30
Advice for young people on maintaining a work-life balance 44:26
Dr. Nina Kottler is the associate chief medical officer of clinical artificial intelligence and vice president of clinical operations for Radiology Partners, the largest radiology practice in the US, serving over 3,250 hospitals and other healthcare facilities, interpreting over 53 million exams annually.
Host: David Wu
Twitter: @davidjhwu
Audio Producer: Aaron Schumacher
LinkedIn: Aaron Schumacher
Video Editor + Art: Saurin Kantesaria
Instagram: saorange314
00:00:58 What brought you to the intersection of medicine and artificial intelligence?
00:07:00 The importance of translating between clinicians and AI engineers
00:12:54 The origins of Radiology Partners
00:16:40 Dr. Kottler’s start in Teleradiology
00:21:18 The transition form analog to digital in Radiology
00:27:35 The current state of Radiology Partners
00:32:00 When did Dr. Kottler become a leader in the AI projects?
00:45:00 AI models that Radiology Partners use
00:52:00 Fragility, Technological Evaluation and Business evaluation in Radiology AI systems
00:56:10 Dr. Kottler’s thoughts on what the future of AI and Radiology will look like.
01:00:30 Dr. Kottler’s advice for people in medicine desiring unique paths.
01:02:45 What brings you joy?
Munjal Shah is the co-founder and CEO of Hippocratic AI, a new startup in Generative AI + Healthcare. Hippocratic is building a safety-focused large language model specifically built for the healthcare industry.
Host: David Wu
Twitter: @davidjhwu
Audio Producer: Aaron Schumacher
LinkedIn: Aaron Schumacher
Video Editor + Art: Saurin Kantesaria
Instagram: saorange314
Time Stamps:
00:00:58 What brought you to the intersection of medicine and artificial intelligence?
00:06:20 Overview of the American Healthcare System
00:08:06 Hippocratic AI and the Adherence Problem within healthcare
00:14:30 Building an AI Chronic Care Nurse for specific conditions
00:17:15 AI systems and medical co-morbidities
00:24:00 The process of building Hippocratic AI
00:32:45 Becoming more efficient than ChatGPT4
00:33:48 Navigating the problem of hallucinations with Hippocratic AI
00:39:30 How close are we to Health General Intelligence (HGI)?
00:45:40 What advice would you give to someone interested in starting their own company?
00:48:20 How did mentorship shape your path?
00:49:40 What brings you joy?
00:52:25 How do you find novel ideas for start-ups?
Dr. Mamdani is a professor, pharmacist, and epidemiologist. He is the Vice President of Data Science and Advanced Analytics at Unity Health Toronto and Director of the University of Toronto Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM). Dr. Mamdani’s team bridges advanced analytics including machine learning with clinical and management decision making to improve patient outcomes and hospital efficiency. Dr. Mamdani is also Professor in the Temerty Faculty of Medicine, the Leslie Dan Faculty of Pharmacy, and the Institute of Health Policy, Management and Evaluation of the Dalla Lana School of Public Health at the University of Toronto. He is also a Faculty Affiliate of the Vector Institute. He has published over 500 studies in peer-reviewed journals.
Host: Raeesa Kabir
Audio Producer: Melanie Bussan
Video Editor + Art: Saurin Kantesaria
Instagram: saorange314
Social Media: Nikhil Kapur
Time Stamps:
0:00 Dr. Mamdani’s Background and Career Path
9:30 Where current data driven medicine strategies fall short and how AI can step in
17:00 How Dr. Mamdani’s work in AI and machine learning began
22:00 Applied Health Research Center and the Ontario Policy Research Network
28:45 The impact of utilizing machine learning and AI at the level of patient care - Chart Watch
35:50 Logistics of Developing and Implementing AI solutions
39:10 Insights Gained - From Purpose to Implementation
43:30 Directing Multiple Projects - Recruitment of AI Team
47:45 Future Projects: Back to AI Basics
54:15 Future of AI in Medicine - Fostering trust in AI
57:20 Advice to Younger Self
CardinalKit (now Spezi) is an open-source framework for Digital Health Applications and Research. They were recently featured in the news for releasing HealthGPT, an experimental iOS app that lets you query your health data. Spezi is housed in the Stanford Byers Center for Biodesign and directed by Oliver Aalami, MD with Vishnu Ravi, MD as lead architect. Also joining us on this interview is postdoc Paul Schmiedmayer, PhD.
Spezi provides a suite of tools to build modern, interoperable digital health tools from the ground up, from the app itself to storing and analyzing collected data in the cloud. It is designed to accelerate rapid prototyping of digital health applications by reducing costs by as much as 75% (~$150,000) and timelines by 12 months.
Host: David Wu
Twitter: @davidjhwu
Audio Producer + Video Editor + Art: Saurin Kantesaria
Instagram: saorange314
Social Media: Nikhil Kapur
Time Stamps:
00:58 - The expertise behind Spezi (CardinalKit)
08:03 - Healthcare has a lack of data standardization + Why you should know about HL7 FHIR
14:13 - How did Spezi (CardinalKit) become what it is today?
18:26 - Drink Spezi!
19:53 - Making code/healthcare data more modular and user-friendly
26:40 - Translating a med student's sensor research to a useable device for kids with cerebral palsy
31:20 - From a $40,000 eczema patch test in clinic to a completely at-home test
35:45 - Using healthGPT to make health data easy to understand for patients (LLM on FHIR)
42:35 - How do you deal with privacy issues?
49:33 - What do you think the future of AI in medicine will look like in 10-20 years?
52:00 - Applications where using only an LLM doesn't always work (a case for hybrid systems)
55:30 - What brings you joy?
58:43 - What makes a successful digital health team?
Dereck Paul, MD is a cofounder and the CEO of Glass Health, an AI-powered medical knowledge management and clinical decision-making platform that helps clinicians provide better patient care. Previously, he was an internal medicine resident at Brigham and Women's Hospital, Harvard Medical School and a medical student at the UCSF School of Medicine.
Host: David Wu
Twitter: @davidjhwu
Audio Producer + Video Editor + Art: Saurin Kantesaria
Instagram: saorange314
Social Media: Nikhil Kapur
Time Stamps:
01:13 - From music major to med school to making a startup
06:30 - Poor healthcare technology = physician burnout, the motivation for building Glass Health
09:15 - Glass Notebook - "Notion for doctors"
11:24 - Building a startup in the era of Chat-GPT
13:50 - What doctors need in an AI-assisted diagnosis software
19:15 - Transition towards a more AI oriented technology - Glass AI
23:00 - How does Glass AI make accurate diagnoses?
28:40 - Why doctors need to be involved in building clinical AI products
30:50 - Practical usage of Glass AI in the clinic
33:04 - Why Glass AI will be more trustworthy than Chat-GPT in writing clinical notes
37:43 - Why LLMs don't need to be perfect for use in the clinic
40:28 - Ethical implications of Glass AI and similar products
45:34 - Should we disclose when we use AI to write a clinical note?
49:13 - What do you think the future of AI in medicine will look like in 10-20 years?
52:30 - What brings you joy? What gives your life meaning?
56:10 - Would you ever go back to being a musician?
Jerry Liu is the co-founder and creator of LlamaIndex (formerly known as GPT-Index), an interface that allows users to connect their data to LLM’s such as Chat-GPT. He has a B.S. in Computer Science from Princeton and has worked at companies such as Quora, Uber, and Robust Intelligence prior to starting LlamaIndex.
Host: David Wu
Twitter: @davidjhwu
Audio Producer: Aaron Schumacher
LinkedIn: Aaron Schumacher
Video Editor + Art: Saurin Kantesaria
Instagram: saorange314
Social Media: Nikhil Kapur
Time Stamps:
01:25 The path to starting LlamaIndex + initial ideas
07:09 LLMs like Chat-GPT vs traditional machine learning
10:00 4 steps of traditional machine learning
10:45 How do large LLMs change the game?
14:11 How does LlamaIndex help LLMs work with unstructured data?
18:08 How do you work with gigabytes of private data?
19:57 Organizing words and paragraphs by topic with embeddings
24:55 The importance of structuring data
26:00 3 key abstractions in LlamaIndex
29:25 Medical use cases for LlamaIndex
31:29 Increasing efficiency in medicine
33:25 An AI medical Research Assistant (Insight)
34:31 Other methods of connecting LLMs to data
36:55 What is langchain?
39:56 What work in the AI and LLM space excites you the most?
42:23 Do you ever feel scared about the developments of AI?
43:45 Llamas and Machine Learning
45:36 What do you think the future of AI in medicine will look like in 10-20 years?
47:24 What advice would you give to grad students, med students, and other early career professionals getting into AI and medicine?
Dr. Ryan earned both a doctorate of medicine (M.D.) and master in public health (M.P.H.) degree from the University of Connecticut in 2001. He completed his postdoctoral training at Harvard's Beth Israel Deaconess Medical Center in Boston, including a chief residency and cardiology fellowship. In 2014 Dr. Ryan started Boards and Beyond, an online lecture library used by medical students across the world to prepare for board exams. In 2022, Dr. Ryan sold his company to McGraw Hill and will continue working to build medical education materials.
Host: David Wu
Twitter: @davidjhwu
Audio Producer: Aaron Schumacher
LinkedIn: Aaron Schumacher
Video Editor + Art: Saurin Kantesaria
Instagram: saorange314
Social Media: Nikhil Kapur
Time Stamps:
00:55 - How did you come to create Boards and Beyond
08:00 - What was it like to make videos outside of your specialty
09:30 - The launch of Boards and Beyond
12:22 - Designing the Curriculum for Boards and Beyond
15:10 - Jason Ryan on selling Boards and Beyond to McGraw Hill
16:58 - What is next for Jason Ryan?
18:00 - Who were Jason Ryan’s favorite teachers
19:48 - What makes a good teacher
23:40 - What are your thoughts on the future of artificial intelligence and medical education
30:03 - Thoughts on Khan Academy’s AI-based Khanmigo
31:25 - Jason Ryan’s thoughts on becoming a clinician
35:29 - Mentorship throughout Jason Ryan’s career
37:35 - Could medical training be shortened?
41:40 - What do you think the future of medicine and artificial intelligence will look like?
43:10 - What advice would you give medical students today?
46:14 - What brings you joy and meaning? What are your greatest fears?
52:48 - What was your lowest point in medical training and how did you overcome it?
Mushtaq Bilal is a postdoctoral researcher at the University of Southern Denmark. He earned his PhD in comparative literature from Binghamton University. He works on simplifying the process of academic writing and writes about ethical use of artificial intelligence for academic purposes.
Host: Raeesa Kabir
Audio Producer: Melanie Bussan
Video Editor + Art: Saurin Kantesaria
Instagram: saorange314
Social Media: Nikhil Kapur
Music: Caligula - Windows96. Used with Artist's Permission.
Introduction and Mushtaq’s path: 0:00 seconds
Overview on using AI tools for efficient writing: 8:00 seconds
Keeping up to date with all the new apps: 18:00 seconds
Leveling the playing field of academia: 23:15 seconds
Ethical considerations of AI powered writing tool: 40:30 seconds
Mushtaq’s tutorial for simplifying the academic writing process: 53:20 seconds
Fun ending question and ending: 57:30
John Kang, MD, Ph.D. is an assistant professor of Radiation Oncology and Biomedical Informatics Lead at the University of Washington in Seattle. His research interests include the application of Natural Language Processing (NLP) to examine trends in the MaML space. He is a physician-data scientist passionate about uncovering the complex interactions underneath large datasets. He has over 10 years of experience in the novel applications of computational modeling and machine learning in biology systems.
Host: David Wu
Twitter: @davidjhwu
Audio Producer: Aaron Schumacher
Twitter: a_schu95
Video Editor + Art: Saurin Kantesaria
Instagram: saorange314
Social Media: Nikhil Kapur
00:45 Could you tell us about your journey to the intersection of medicine and machine learning
07:40 Balancing Residency Training and staying caught up on research in the machine learning space
16:00 Using machine learning to understand biostatistics
18:12 How would you describe the research that you find the most exciting / Unsupervised learning
23:00 Overview of Word Embedding and addressing potential bias
29:25 Dr. Kang’s application of word embedding for research funding
42:52 The intersection of artificial intelligence and human intelligence
45:35 T-SNE / T-Distributed Stochastic Neighbor Embedding in grant analysis
50:50 Has T-SNE helped guide Dr. Kang’s research and grant writing
57:00 The future of creativity and ChatGPT
01:02:30 Fear vs Hope in the Medicine and Machine Learning space
01:07:00 What do you think is the future of the MaML space in the next 10-20 years?
01:11:02 What advice would you give yourself as you were finishing medical school?
Welcome back to the third season of the medicine and machine learning podcast! We are kicking off our year with a very unique episode. Our "guest" is ChatGPT! ChatGPT is an artificial-intelligence chatbot developed by OpenAI and launched in November 2022. Since its launch, ChatGPT has been an internet and media sensation. Usage is currently freely available to the public because ChatGPT is in its research and feedback-collection phase. This open interface has been hugely influential in bringing public attention to how AI can be used as a multidisciplinary resource. In this episode, the MaML team asked some fun questions of ChatGPT and gave the answers a voice with text-to-speech software!
Don’t forget to follow us on twitter @themamlpodcast!
Host and Producer: Madeline Ahern / Twitter @maddie_ahern
Host: David Wu / Twitter: @davidjhwu
Host: Raeesa Kabir
Artwork: Saurin Kantesaria
Music: Caligula - Windows96. Used with Artist's Permission.
00:40 GPT-4's Intro
01:40 The "Path" of ChatGPT
03:20 ChatGPT's advice for passing STEP exams
07:25 GPT-4 Tackles an Ethics Question
12:00 GPT-4 Tackles a STEP 1 Practice Question
14:44 GPT-4 Tackles a Clinical Scenario
19:02 ChatGPT has passed the boards, how would it do on CASPer?
20:15 The future of AI in medicine
27:31 Closing Remarks
Dr Matthew Lungren is the Chief Medical Information Officer at Nuance Communications, a Microsoft Company. As a physician and clinical machine learning researcher, he maintains a part-time interventional radiology practice at UCSF while also serving as adjunct faculty for other leading academic medical centers including Stanford and Duke. Prior to joining Microsoft, Dr Lungren led the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI).
This interview offers great insight for anyone who is interested in non-traditional career paths in medicine at the cutting edge of the MaML space. I hope you all enjoy!
and don’t forget to follow us on twitter @themamlpodcast!
Host: David Wu / Twitter: @davidjhwu
Producer: Aaron Schumacher / Twitter: @a_schu95
Artwork & Video: Saurin Kantesaria
Music: Caligula - Windows96. Used with Artist's Permission.
00:40 Could you tell us about your path coming to the intersection of medicine and artificial intelligence?
07:00 What literature are you a fan of?
08:50 Where will the next great American Author come from?
14:00 Tell us about your work with Nuance.
17:50 Could you tell us the background of Nuance and Dragon Dictation?
19:55 Tell us about Nuance products that are offered.
23:45 How much code should future physicians know?
28:30 What is a typical day like as chief medical officer
31:30 Do you have any advice for medical students interested in nontraditional career paths?
34:30 How do you balance clinical practice and industry work?
40:40 What are you excited about most in the next 10-20 years?
44:15 How has mentorship shaped your path?
46:08 What advice would you give yourself at your medical school graduation?
Dr. Kaz Nelson is a Fellow of the American Board of Psychiatry and Neurology and serves as Associate Professor in the Department of Psychiatry and Behavioral Sciences and the Associate Designated Institutional Official in the Office of Graduate Medical Education at the University of Minnesota Medical School. She is also host of “The Mind Deconstructed.” In this podcast, Nelson and her brother George dispel myths, address listener questions, and inform the public about mental health and a life worth living.
Connect with Dr. Nelson on the following platforms:
Twitter: @kazjnelson
Facebook: @kazjnelson
Youtube: The Mind Deconstructed
Host: Madeline Ahern @maddie_ahern
Producer: Kirsi Oldenburg
Artwork & Video: Saurin Kantesaria
Music: Caligula - Windows96, Used with artist permission
01:13 Introduction - Dr. Kaz Nelson
06:20 Sacrifices of Physicians (and their families)
08:25 Limitations of the Mental Health System
13:00 AI Chatbots: Helpful or Harmful?
23:00 High-Acuity Care and Psychiatric Crises
30:30 First Interactions with the Mental Health System
37:10 The Mind Deconstructed
43:45 The Future of AI, Chat GPT
47:30 The Pull of the Status Quo
53:24 Advice to our Listeners
Dr. John Sargent: Dr. John Sargent is the co-founder of BroadReach Group and an internationally recognized thought leader who brings extensive experience in health systems strengthening large-scale patient education programs and the creation and implementation of public-private partnerships in emerging markets. Prior to co-founding BroadReach Group, he obtained his Doctor of Medicine from Harvard Medical School and gained experience as a strategic and operational consultant with expertise spanning multiple disease areas across public and private health sectors.
Annika Krugel: Annika Krugel is the Client Director for Vantage Health Technologies, which is a platform from BroadReach that uses AI to aggregate all data in an area or a clinic and then give individualized decision support, operational tools, and step-by-step workflows to empower healthcare workers. Annika has a Master’s Degree in Development Studies and has 15 years of experience across civil society and the public- and private sectors in various roles but always in a coordinating capacity.
1:15- Journey to the intersection of medicine and
9:00- Foundation of the BroadReach Group and current work
23:00- Inception of Vantage Health Technologies
25:20- Vantage Health Technologies’ role in the pandemic response
35:30- BroadReach Group and Vantage Health Technologies’ overall work across the globe
37:00- Future work
45:00- Future of big data and AI in medicine
50:30- Ensuring patient data privacy and security
52:30- Advice and ending thoughts
Dr. Joe Zhang is an Intensive Care doc and health data scientist. He holds a Wellcome Trust fellowship in health informatics and artificial intelligence (AI) at Imperial College London. He has extensive experience in developing and deploying informatics and data solutions in the NHS, and is currently working at the intersection of data science, policy, and infrastructure.
Host: David Wu / Twitter: @davidjhwu
Producer: Aaron Schumacher / Twitter: @a_schu95
Artwork & Video: Saurin Kantesaria
Music: Caligula - Windows96. Used with Artist Permission.
1:10 Your path to the intersection of Medicine and Machine Learning
4:45 What Electronic health records are used in the UK and how does the NHS operate?
12:40 Who uses the data you gather in the NHS?
12:40 Could you tell us about your new publication on the vertical translation of data in AI?
28:00 Can you speak to regulatory bodies and the implementation of AI into healthcare?
32:00 The global clinical AI dashboard
37:25 Any future projects in the pipeline?
39:00 What projects tend to have the most success at being integrated into healthcare?
41:08 How has mentorship shaped your path?
42:15 What do you think the future of AI in medicine will look like in 10 to 20 years?
46:50 What brings you joy and meaning?
48:00 Closing thoughts for the listeners
Ittai Dayan, MD is the co-founder and CEO of Rhino Health, a distributed computing platform leveraging privacy-preserving federated learning. The platform allows medical researchers and healthcare AI developers to seamlessly access diverse and disparate datasets and use them to create better AI algorithms.
contact@themamlpodcast.com
Host: David Wu / Twitter: @davidjhwu
Producer: Aaron Schumacher / Twitter: @a_schu95
Artwork & Video: Saurin Kantesaria
Music: Caligula - Windows96. Used with Artist Permission.
00:56 How did you come to the intersection of medicine and artificial intelligence?
06:15 What type of medicine did you start out studying?
11:35 Could you tell us the story behind Rhino Health?
14:30 What is federated learning?
21:00 Common use cases for Rhino Health?
26:45 Relationship between generalizability and accuracy when using federated learning?
28:15 What were your biggest challenges in creating Rhino Health?
32:40 An example of using Rhino Health?
37:40 How does Rhino Health integrate with EHR’s
38:15 What are your next steps for Rhino Health?
43:10 What do you think the future of AI in healthcare will look like?
48:08 What gives your life meaning and what are your greatest fears?
