The Physician AI Handbook

Peer-Reviewed Evidence Across Every Medical Specialty

What works. What doesn’t. What happens when AI is wrong.
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Updated

October 2026 · Changelog

Welcome to The Physician AI Handbook

AI performance in real-world clinical settings often falls short of published validation studies. Written by a physician for clinicians, health system leaders, and anyone building or deploying clinical AI.

Three questions drive this handbook: What does the peer-reviewed evidence actually show? How do you evaluate claims against that evidence? What are the medico-legal implications when AI is wrong?

This resource is continuously updated as new research emerges.

Important Disclaimers

This handbook is for educational and informational purposes only. It does not provide medical advice, diagnosis, or treatment. AI systems discussed here are decision-support tools, not substitutes for clinical judgment.

Clinical use remains context-specific. Physicians should validate AI outputs before clinical use, follow applicable FDA and HIPAA requirements, and meet the standard of care in their jurisdiction.

Information may become outdated as AI tools, evidence, and clinical guidelines change. Verify recommendations with current clinical guidance before application.

This handbook does not provide legal advice. Consult qualified legal counsel for questions about malpractice, liability, and regulatory compliance.


Recent Updates

Start Here

Read the evidence framework first, then the tools.

  1. Executive Summary: Key findings across all specialties
  2. AI Fundamentals for Clinicians: What AI is and how it works
  3. AI Physician Toolkit: Tools for daily clinical practice

Then continue to Evaluating AI Systems before adopting any tool.

For specialty-specific reading paths, see the Preface.

An AI assistant helping you should follow the Guidance for AI Agents.


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Free to read and reuse under CC BY 4.0 · DOI 10.5281/zenodo.18251405 · How to cite

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