By Twitter - @themamlpodcast | TikTok - @maml_podcast
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The podcast currently has 51 episodes available.
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
The podcast currently has 51 episodes available.
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