Freddy Abnousi

#AtroposHealth announces the world's largest body of medical evidence. Alexandria®, the Atropos Evidence™ Library now exceeds 33M artifacts for clinical decision support and LLM training with a path to 2B by end of 2026. Learn more: hubs.li/Q04cWhjk0 #HealthcareContent

@chukanyaegbuna @CelinaMYongMD @statnews Thank you!

@FAbnousi @CelinaMYongMD @statnews Beautiful

Medicine was built on the medical record. But most of health and illness happens outside of it. AI doesn’t create that gap — it exposes it. The question now is structural: where should this data live — under what rules, and for whose benefit? With @CelinaMYongMD in @statnews:

@PsudoMike @_jasonwei There are a lot of hard problems here — this is one of them. Even if the models and pipelines work, how do you integrate this into workflow without flooding the system? We’re still trying to fit something fundamentally different into structures built around the record.

@_jasonwei @FAbnousi The hard engineering here lives in the pipeline more than the model. Ingesting 24/7 wearable streams, deduping, aligning to episodes, and surfacing what's actionable is where it breaks. That stack doesn't exist at scale yet.

Beautifully written piece by @FAbnousi about how AI for health might look like in the future The current data in health is limited because it only captures episodic clinical snapshots of what happens to our bodies The revelation is that there is so much latent knowledge in looking at regular changes in our body. Could be through lab tests or even proxy metrics like wearable data With AI democratizing the ability for people to understand their own health, we're moving towards a trend of individuals gathering health data around their bodies and leveraging AI to understand themselves Bryan Johnson is extreme but a good example of this trend Personally, I started getting Function Health blood tests every six weeks instead of the recommended six months to increase fidelity on how changes in lifestyle affect my body Of course i use AI to analyze the results and adapt, and it's been great It would be cool to something in this direction happen in a big way across the world And welcome to twitter @FAbnousi!

@_jasonwei appreciate the read — and the example. Feels like the core issue is that medicine was built around the medical record — episodic, structured, and largely institutional. Most of health and illness actually unfolds outside of that. Continuous data helps, but the real shift is making that lived experience visible.

Now unlocked — full piece here: statnews.com/2026/04/16/med…

Update: STAT has now removed the paywall — full piece is accessible here: statnews.com/2026/04/16/med…

AI knows medicine. It doesn’t know patients. Every day, we ask patients to reconstruct a life they were busy living, not recording. A patient moves through the health care system like a traveler through airports — each stop generates a new record, rarely connected to the rest of the journey. Medicine has learned to interpret records — but not the life that produces them. With @CelinaMYongMD in @statnews.

@westr @statnews Thanks for the kind words!

GENIUS: The medical AI revolution requires rethinking health care’s architecture statnews.com/2026/04/16/med… via @statnews #PM101 “The first era of digital health focused on digitizing medical records. The next era will be defined by something more difficult: deciding how the data of a human life should be structured, governed, and interpreted. Artificial intelligence will transform how medicine reasons, but the systems that organize the data will determine how far that transformation can go.”