AI is not a medical expert. AI is a pseudo expert. It possesses incredible a capacity to scour all of the available information and put together a coherent answer or summary. This answer or summary will greatly help the general public and physicians who are not experts in a given disease by making search, retrieval, synthesis of available information. But it’s not an expert. AI cannot be expected to know data that’s known to experts but is not yet published. It cannot know when data in published form differs from that experienced in real world practice by clinicians who see a large volume of patients with the same disease. Where the published data are wrong or exaggerate benefits or minimize risks. It cannot judge the right treatment option among similar competing treatment options (except superficially), especially based on what the patient evaluation reveals on history and examination. AI appears to be an expert in everything in the world by knowing what experts have written and made public but lacks wisdom by the very nature of how it works to produce the answer. It’s not thinking. It knows as the famous saying where the puck is but not where it’s going to be. That’s why the even the most ardent proponents of AI including the uber rich who own the models will always seek out the best human expert available for serious diseases. They may use AI to provide a summary of their disease for the expert but they are not going to mistake or substitute AI for the expert. I don’t see this changing. Because medicine is more than knowing everything that’s published or being able to retrieve it quickly. We live in a world of medicine where it’s easy to confuse pseudo experts who have gained or granted prominence with real depth of expertise and wisdom. So it’s easy to see how a lot of us are mesmerized by the speed and eloquence of AI to answer queries. Yes it does that well (and is probably sufficient 90% of the time). But as you learn how LLMs and other AI tools work you know it’s no expert, but a useful side kick. I do think it can help both experts and non experts but we must know what it’s capable of and what it’s not.

Important work @iStopMM @BloodCancerJnl #mmsm New study from iStopMM screened >75000 people for MGUS ✅ >27000 completed a food survey — 1,020 had MGUS ✅ Overall diet & dietary patterns are NOT major risk factors for MGUS(imp finding) 🛑Exception: High dairy intake was linked to 2x higher odds of IgA MGUS (OR 2.01) Bottom line: What you eat likely isn't driving your multiple myeloma risk — but dairy's role in IgA MGUS is an interesting finding ➡️ nature.com/articles/s41408-0…

Researchers propose the removal of an sFLC ratio ≥100 as a standalone myeloma-defining event in the IMWG diagnostic criteria for #MMsm, as new findings indicate the previously cited 80% risk of disease progression at two years may be substantially lower: ow.ly/TpF750YwhlS