AI in Healthcare: What AI Can and Can't Tell You About Your Health | Nasim Afsar, MD, MBA

One of the biggest problems with healthcare isn't a lack of data, but the fact that none of it is connected. We have lab results, wearables, environmental exposures, sleep scores, and medical records scattered in different places. Yet we're often left without a clear picture of what all that information actually means for our health.

I sat down with Nasim Afsar to explore how artificial intelligence could help us bring those pieces together. We talked about using tools like Claude and Gemini for health questions, the limitations of today's AI models, privacy concerns, and why relying too heavily on numbers can disconnect you from what your body is telling you.

We also look at where healthcare is headed, from continuous monitoring and predictive analytics to personalized prevention before symptoms become bigger problems. You'll hear about how to filter through biohacking noise, make smarter decisions with your health data, and use technology without letting it replace your own judgment.

"Large language models have access to a wealth of information that can help you better understand what your information says, and potentially brainstorm about what else could be going on." ~ Nasim Afsar

In This Episode:

- The pillars of intelligent health

- Using AI to analyze complex health symptoms

- Best LLMs and wearables for health data

- Avoiding health optimization overload

- Monitoring and consolidating data for health intelligence

- Bias in AI recommendations

- How algorithms shape health information