Discover the newest research about AI innovations in 🧠LLM’s.
A new AI system called MedGenesis can compress years of clinical research into hours by autonomously generating hypotheses and analyzing patient data.
Using artificial intelligence to grade medical answers backfires because algorithms prefer long-winded fluff over actual clinical accuracy.
Automating cancer registries with artificial intelligence sounds like an easy win, but new data shows these models fail at the precise timelines crucial for tracking patient care.
Ambient clinical AI is no longer just a digital scribe; it is actively inserting itself into financial and medical decisions.
A new study reveals that even the smartest medical AI models cannot accurately judge when they are wrong.
Most clinical AI models fail when they leave their home hospital, but a new 26-model suite proves that reproducible clinical tools can survive the transition to different healthcare systems.
By feeding raw smartphone eye-tracking data into off-the-shelf language models, researchers bypassed the need for custom medical AI to spot Huntington’s disease.
Regulators are clearing the path for AI that writes its own clinical notes, shifting the technology from a simple second pair of eyes to an active administrative partner.
A new language model attempts to solve a major diagnostic bias by separating normal hormonal transitions from actual viral damage in women.
Hiring a commercial AI to read breast cancer biopsies does not just introduce errors; it forces clinicians to choose which specific flavor of diagnostic failure they can tolerate.
