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Role of Large Language Models in AI-driven medical research | Dr. Imon Banerjee
Dr. Imon Banerjee is an Associate Professor at Mayo Clinic in Arizona, working at the intersection of AI and healthcare research. Her research focuses on multi-modality fusion, mitigating bias in AI models specifically in the context of medical applications & more broadly building predictive models using different data sources. Before joining the Mayo Clinic, she was at Emory University as an Assistant Professor and at Stanford as a Postdoctoral fellow.
Time stamps of the conversation
00:00 Highlights
01:00 Introduction
01:50 Entry point in AI
04:41 Landscape of AI in healthcare so far
06:15 Research to practice
07:50 Challenges of AI Democratization
11:56 Era of Generative AI in Medical Research
15:57 Responsibilities to realize
16:40 Are LLMs a world model?
17:50 Training on medical data
19:55 AI as a tool in clinical workflows
23:36 Scientific discovery in medicine
27:08 Dangers of biased AI models in healthcare applications
28:40 Good vs Bad bias
33:33 Scaling models - the current trend in AI research
35:05 Current focus of research
36:41 Advice on getting started
39:46 Interdisciplinary efforts for efficiency
42:22 Personalities for getting into research
More about Dr. Banerjee's lab and research: https://labs.engineering.asu.edu/banerjeelab/person/imon-banerjee/
About the Host:
Jay is a PhD student at Arizona State University.
Linkedin: https://www.linkedin.com/in/shahjay22/
Twitter: https://twitter.com/jaygshah22
Homepage: https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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By Jay Shah
5
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Dr. Imon Banerjee is an Associate Professor at Mayo Clinic in Arizona, working at the intersection of AI and healthcare research. Her research focuses on multi-modality fusion, mitigating bias in AI models specifically in the context of medical applications & more broadly building predictive models using different data sources. Before joining the Mayo Clinic, she was at Emory University as an Assistant Professor and at Stanford as a Postdoctoral fellow.
Time stamps of the conversation
00:00 Highlights
01:00 Introduction
01:50 Entry point in AI
04:41 Landscape of AI in healthcare so far
06:15 Research to practice
07:50 Challenges of AI Democratization
11:56 Era of Generative AI in Medical Research
15:57 Responsibilities to realize
16:40 Are LLMs a world model?
17:50 Training on medical data
19:55 AI as a tool in clinical workflows
23:36 Scientific discovery in medicine
27:08 Dangers of biased AI models in healthcare applications
28:40 Good vs Bad bias
33:33 Scaling models - the current trend in AI research
35:05 Current focus of research
36:41 Advice on getting started
39:46 Interdisciplinary efforts for efficiency
42:22 Personalities for getting into research
More about Dr. Banerjee's lab and research: https://labs.engineering.asu.edu/banerjeelab/person/imon-banerjee/
About the Host:
Jay is a PhD student at Arizona State University.
Linkedin: https://www.linkedin.com/in/shahjay22/
Twitter: https://twitter.com/jaygshah22
Homepage: https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***