AI Doctors for Virtual Patient Diagnosis

Can an # AI #Doctor partner with clinicians? Can we please move past the AI versus doctor/clinician comparisons in taking board exams.. solving diagnostically challenging cases... providing more empathetic on-line responses to patients...? and instead focus on improving patient care and their outcomes? The authors, Hashim Hayat, Adam Oskowitz et. al. at the University of California, San Francisco, of a recent study may be hinting at this: envisioning an agentic model (Doctronic) “used in sequence with a clinician” to expand access while letting doctors focus on high‑touch, high‑complexity care and supporting the notion that AI’s “main utility is augmenting throughput” rather than replacing clinicians (https://lnkd.in/e-y3CnuF)  In their study: ▪️ >100 cooperating LLM agents handled history evaluation, differential diagnosis, and plan development autonomously. ▪️ Performance was assessed with predefined LLM‑judge prompts plus human review. ▪️ Primary diagnosis matched clinicians in 81 % of cases and ≥1 of the top‑4 matched in 95 %—with no fabricated diagnoses or treatments. ▪️AI and clinicians produced clinically compatible care plans in 99.2 % of cases (496 / 500).  ▪️In discordant outputs, expert reviewers judged the AI superior 36 % of the time vs. 9 % for clinicians (remainder equivalent). Some key #healthcare AI concepts to consider: 🟢 Cognitive back‑up, in this study, the model identified overlooked guideline details (seen in the 36 % of discordant cases; the model used guidelines and clinicians missed). 🟢 Clinicians sense nuances that AI cannot perceive (like body‑language, social determinants). 🟢 Workflow relief , Automating history‑taking and structured documentation, which this study demonstrates is feasible, returns precious time to bedside interactions. 🟢 Safety net through complementary error profiles – Humans misdiagnose for different reasons than #LLMs; so using both enables cross‑checks that neither party could execute alone and may have a synergistic effect. Future research would benefit from designing trials that directly quantify team performance (clinician/team alone vs. clinician/team + AI) rather than head‑to‑head contests, aligning study structure with the real clinical objective—better outcomes through collaboration. Ryan McAdams, MD Scott J. Campbell MD, MPH George Ferzli, MD, MBOE, EMBA Brynne Sullivan Ameena Husain, DO Alvaro Moreira Kristyn Beam Spencer Dorn Hansa Bhargava MD Michael Posencheg Bimal Desai MD, MBI, FAAP, FAMIA Jeffrey Glasheen, MD Thoughts? #UsingWhatWeHaveBetter

Autonomous AI now matches doctors in 81% of urgent care visits. Doctronic has released early findings from its large-scale, real-world evaluation of an autonomous multi-agent AI framework operating as a virtual urgent care provider. The study benchmarked 500 consecutive patient encounters between the system and board-certified physicians. Diagnostic agreement occurred in 81% of cases, treatment plan alignment reached 99.2%, and no hallucinated diagnoses or treatments were recorded. In a blind review of mismatches, clinical experts rated the AI superior in 36.1% of cases, with humans leading in 9.3%. All authors disclosed equity ownership in the company. Topline outcomes point to enterprise-ready levels of accuracy in clinical decision-making without human oversight. 👉 Follow me, Harold Hare, for AI-driven healthcare disruption metrics. ⬆️⬆️⬆️ Reference: Hayat, H., Kudrautsau, M., Makarov, E., Melnichenko, V., Tsykunou, T., Varaksin, P., Pavelle, M., & Oskowitz, A. Z. (2025). Toward the autonomous AI doctor: Quantitative benchmarking of an autonomous agentic AI versus board-certified clinicians in a real world setting. bioRxiv & medRxiv. #Healthcare #AI #Doctronic #medRxiv #HaroldHare

On July 16, 2025, a small San Francisco outfit named Doctronic dropped a preprint that didn't just hint at the future, it walked into the exam room and wrote its own chart note. Titled "Toward the Autonomous AI Doctor," this wasn't theory or vapor. This was 500 real telehealth urgent-care encounters, evaluated head-to-head against board-certified #physicians. No rehearsal, no training wheels. Just a #multiagent LLM system diagnosing, treating, and documenting, all without a single real-time human prompt. The numbers snapped heads: 81% diagnostic concordance, 99.2% #treatmentplan alignment, and zero clinical hallucinations. In the 13.4% of cases where Doctronic and doctors disagreed, the AI's plan outperformed the human one nearly 4 to 1. That's not a marginal gain. That's a paradigm crack. The kind that tells you the algorithm isn't coming, it's already here, in scrubs, with a badge clipped on. Founded in 2024, Doctronic Inc. wasn't born from a whiteboard brainstorm. It was built by product-hardened #engineers and AI obsessives who knew the problem wasn't intelligence, it was autonomy. CEO Hashim Hayat steered product strategy with clinical realism, while CTO Maksim Kudrautsau and Chief Architect Evgeniy Makarov wired the system with a multi-agent architecture tight enough to pass medical muster. Clinical validation wasn't an afterthought, it was frontloaded under the guidance of University of California, San Francisco's ADAM ZEV OSKOWITZ, MD, now Chief Medical Officer. This isn't another #AIassistant whispering in a doctor's ear. This is a standalone agent that listens, thinks, and acts, end-to-end, across urgent-care use cases. It pulls history, parses imaging, generates differentials, and drops treatment plans that stack up to board-certified care. Doctronic doesn't augment the #clinician. It does the job. The market? Massive. The timing? Now. With $8 million in seed financing and pilots underway with UCSF's telehealth division, Doctronic is sliding into a space few dare touch: real autonomy. The healthcare AI market, pegged at $15 billion in 2025, is sprinting toward $50 billion by 2030. Legacy giants like IBM Watson Health and Google DeepMind's MedPalm Clinic talk autonomy. Doctronic ships it. Eyes now turn to what's next: FDA 510(k) filing by year's end, CMS policy shifts around AI reimbursement, and deeper integration with EHR juggernauts like Epic and Cerner Corporation. Meanwhile, the team's already building modules for #chroniccare and specialty triage. Urgent care was the test. The real game's just begun. If you're in healthtech and not watching Doctronic, you're missing the move. #Startups #StartupNews #Telehealth #Diagnostics #HealthTech #Healthcare #DeepTech #Technology #Innovation #TechEcosystem #StartupEcosystem #TechNews If engineering peace of mind is what you crave, Vention is your zen.