Can AI Diagnose Better Than Humans?

A week ago, Microsoft released the AI Diagnostic Orchestrator (MAI-DxO), a platform designed to utilize five large language model agents functioning as a panel of virtual doctors to develop disease treatment strategies. To evaluate its capabilities, the Orchestrator was tested using 304 medical case studies sourced from the New England Journal of Medicine. MAI-DxO pushed OpenAI’s latest o3 model to solve 85.5% of them, quadrupling the success rate reported for experienced clinicians working under identical constraints.

This launch echoes the words of medical futurist Bertalan Meskó who once called artificial intelligence the “the stethoscope of the 21st century”. But AI diagnostics didn’t start with LLMs, it goes back to the 1950s, with rule-based systems and early diagnostic logic.

In this article: How Diagnostic AI Got Here — Tradition vs. Modernity — Molecular Diagnostics — Cancer Diagnostics — Infectious Diseases — Rare Genetic Diseases — Clinical Imaging — Cardiovascular Diseases — Dermatology — Respiratory Diseases — Eye Diseases — Digital Pathology — Prospects & Challenges