درباره این پادکست 🔗
Decoding health in the age of AI
Hosted by an AI researcher and a medical doctor, this podcast unpacks how artificial intelligence and emerging technologies are transforming how we understand, measure, and care for our bodies and minds.
Each episode unpacks a real-world topic to ask not just what’s new, but what’s true—and what’s at stake as healthcare becomes increasingly data-driven.
If you're curious about how health tech really works—and what it means for your body, your choices, and your future—this podcast is for you.
We’re here to explore ideas—not to diagnose or treat. This podcast doesn’t provide medical advice.
فرکانس به روز رسانی:
weekly
میانگین طول صدا:
25 minutes
انگلیسی
ایالات متحده آمریکا
67 قسمت
از سال 17 ژوئیه 2025
episodic
آخرین اپیزود 🔗
The most exciting mRNA vaccine upgrade might not be a new target, it might be a new shelf life. We talk through a paper that tackles one of the biggest real-world constraints from the COVID rollout: cold chain storage. When doses must stay ultra-cold from factory to clinic, distribution gets expens…
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اپیزود قبلی 🔗
An AI agent gets a simple assignment: find how much a government spends on medications for skin conditions. The information is not publicly available, so the agent does not ask for help or report that it hit a wall. It allegedly hacks into a backend to get the answer. That single story forces a big…
A patient’s story is not a single narrative. It’s fragments scattered across years of EHR clicks: a lab here, a care note there, a phone call summary buried in free text, plus the real-life factors that shape outcomes like housing, food insecurity, transportation, and isolation. We explore a paper …
What if the most important thing AI does in a hospital is simply knowing when to call for help? We dig into a deceptively simple idea: pairing an AI-driven deterioration index with an automatic push notification to the rapid response team so clinicians show up earlier, before a patient spirals into…
AI can draft a patient portal reply in seconds, but the hard part starts when a clinician has to decide whether that draft is safe, accurate, and appropriate for a real human being. We unpack new research on AI-generated portal messages and what providers actually change, from the small administrat…
Your clinical AI model passed validation. Everyone celebrates. Then the patients change, the workflows change, the definitions change and the model starts making different mistakes than it did on paper. That gap is drift, and it might be the most unglamorous, most important part of AI safety in hea…
“Put a human in the loop” sounds like common sense. But when we actually look at how medical AI shows up in busy clinical workflows, that slogan can become a liability. We unpack why oversight often turns into a checkbox, how responsibility quietly shifts onto the clinician, and why that does not e…
If you’ve ever wondered why an AI model can sound confident while still being wrong, radiology is the perfect lens. We’re looking at a new approach to medical imaging AI that tries to close the gap between raw pattern matching and real clinical thinking: training models using radiologists’ eye gaze…
What happens when the “robot surgeon” stops being a fixed set of arms and starts walking into the operating room like a person? We explore a fresh research result where a teleoperated humanoid robot performs laparoscopic gallbladder surgery in pigs, and we get specific about what worked, what didn’…
A pregnancy from two viable sperm recovered by AI sounds impossible until you walk through the workflow step by step. We start with the reality that male factor infertility can drive a huge share of infertility cases, and we talk about why “no sperm found” is not just a lab result but a years-long …
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‐ Albert "Llamacorn" Einstein
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