This is a critically important episode for all physicians, not just genetics and metabolism experts. Well done!

Self-attention in LLMs, clearly explained:

Interesting article. The "three performance regimes" subjectively correlate with my practical experience: 1. low-complexity: standard models outperform LRMs 2. medium-complexity: LRMs demonstrate advantage 3. high-complexity: both experience collapse machinelearning.apple.com/research/illus…

I'm grateful for the opportunity to be a part of this work from my radiology colleagues here Vanderbilt Health rdcu.be/epVw8

Unexplained Progressive Respiratory Insufficiency and Weakness Diagnosed as Late-Onset Pompe Disease Through Biochemical and Molecular Genetic Testing journals.sagepub.com/doi/10.1177/19…

I'm curating genes to add to an inborn errors of immunity panel. o3 did a pretty thoughtful job of explaining why to add some on the 2024 IUI list (not sure yet about FOXI3) I need to look at the rest of the list still to see if any were missed that may have sufficient evidence

I find the story of AI and radiology fascinating. Of course, Hinton's prediction was wrong* and tech advances don't automatically and straightforwardly cause job replacement — that's not the interesting part. Radiology has embraced AI enthusiastically, and the labor force is

This is interesting because if you substitute “medicine” for “software”/“tech” and take “you” to be the plural incorporating yourself, the patient, and the healthcare team, the second paragraph actually well describes practicing medicine

Microsoft claims their new AI framework diagnoses 4x better than doctors. I'm a medical doctor and I actually read the paper. Here's my perspective on why this is both impressive AND misleading ... 🧵