Join host Vahe Andonians in a captivating discussion with Dr. Thomas Fuchs, Department Chair of Artificial Intelligence and Human Health at Mount Sinai, as they delve into the profound impact of artificial intelligence on personalized healthcare and early disease detection.

Exploring vital aspects like the ethical considerations surrounding AI, the potential of hybrid intelligence, and the expanding role of AI in drug discovery and complex data interpretation, Dr. Fuchs underscores the pivotal role of AI as both a tool for physicians and a catalyst for advancements in healthcare.

In addition, Dr. Fuchs addresses the challenges of explainability in AI decision-making compared to human doctors, emphasizes the value of large language models, and explores the potential of AI in delivering previously inaccessible healthcare solutions to remote or underserved areas worldwide.

Key Quotes: 

• “Just to keep the standard of care, you're going to need AI. Then if you go beyond, of course, the U.S. or Europe, there are many areas in the world where we only have one or two pathologists for the whole country, they are completely underserved.  And that's a very good example where AI can lead truly to the democratization of access to healthcare.”
• “The hope remains that we can go beyond human capabilities and that's probably done with other technologies than the human works, right? There's so much pain and suffering in the world and we have an obligation to reduce that if we can build systems, even if they are different than us. Their intelligences are different than ours. If we can deploy them to help patients, we are morally obliged to do so.”
• “Reducing your information input can't possibly lead to a better outcome. So then what you could argue is that there are so many outside constraints, because of processes, procedures, and the healthcare system in general, that more information would lead, for example, to overtreatment. But in general, you should never shoot the messenger, but deal with the message.”
• “What's also important to understand in healthcare, that very often, at least from my machine learning colleagues is that ethics in medicine is, of course, a very old field and you have bioethicists and bioethics groups, in academic medical centers, universities, and healthcare systems, since, a long time and who do ethics in healthcare for decades.”

Time Stamps:

• (2:01) The information tidal wave in healthcare
• (5:39) Bringing LLMs to healthcare research models
• (15:34) Keeping up the ethical standards of healthcare with AI 
• (29:25) Using hybrid intelligence of humans and AI for better healthcare
• (34:50) AI’s impact on research in healthcare
• (39:52) Modeling AI more towards the human brain

Links:

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