The MaML Podcast - Medicine & Machine Learning

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! contact@themamlpodcast.com 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! contact@themamlpodcast.com 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. 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. 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?

Beth Beadle, MD, PhD is the Director of Head & Neck Radiation Oncology at Stanford and co-creator of the Radiation Planning Assistant, a fully automated treatment planning assistant.  00:56 How did you come to the intersection of medicine and AI? 03:20  What is radiation oncology and why does it fit well with AI? 05:54 How has radiation changed in your lifetime? 09:19 What is the Radiation Planning Assistant? 13:10 Describe radiation oncology workflow before the use of the radiation planning assistant 20:45  How does the model compare humans? 23:45 Where was the data source for the radiation Planning Assistant Model? 26:45 What safeguards exist for RPA? 28:00 What has been the response from other physicians, physicists, and patients to this model? 33:30 Timeline for implementation of the radiation planning assistant? 34:45 Background of the Radiation Planning Assistant 38:25 Future of Radiation Planning Assistant implementation 40:55 Adaptive planning in radiation oncology 43:15 Future of the Radiation Planning Assistant in the next 10 years 44:50 Are there any other projects being planned currently? 47:00 How has mentorship shaped your path? 50:25 What is the future of AI in medicine in 10-20 years 51:48 What advice would you tell yourself when you were graduating from medical school 53:20 What brings your life joy and meaning? 54:50 What are your greatest fears? 55:15 Favorite places to travel?