Doctors and patients are now throwing hard cases at frontier models (e.g., GPT-5 Pro) and reporting striking hits—from photo-plus-symptom identifications to prioritized differentials that read like a top subspecialist’s note. The vibe in user stories is awed and practical (“it cracked what stumped us for months”), while experts project a sharper, more split energy: some point to validated wins (sepsis triage, retina-based lupus), agentic systems claiming big accuracy gains, and med-school curricula catching up; others flag nuance—RCTs where “AI alone” beats clinicians but adding it didn’t help, and reminders that diagnosis may soon be commoditized while judgment and management remain the real game. Net: in 2025, AI is moving from clever consult to co-diagnostician—powerful, faster, often right—but still demanding guardrails, evidence, and human stewardship.
🤖 ai summary based on 17 tweets
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A.I. generated clinic notes from ambient out-patient visits helps clinicians in many ways, across 6 health systems https://t.co/wT8fm42H9Q https://t.co/SfSUqDasCG
At @StanfordMed, #AI is becoming part of the curriculum, clinical training and the future of care https://t.co/iZOdpieImD
Large language models forecast patient health trajectories enabling digital twins @npjDigitalMed 10/1/2025 #AI #LLM #DigitalTwins #TechHartford https://t.co/z8vp4E4gEy
A father’s quest for diagnosis inspired a disruptive AI solution https://t.co/w8MONk2ZEM @microsoft