Microsoft's AI diagnostic system correctly identified complex medical cases more than twice as often as generalist doctors in a simulation, according to a study published Thursday in Science. The system, called MAI-DxO, was accurate 83% of the time on difficult cases from the New England Journal of Medicine, while primary care doctors and general internists working alone with reference materials scored 36%.
Mustafa Suleyman, CEO of Microsoft AI, called the result a step toward "medical superintelligence." The company joins Google and OpenAI in claiming its AI can match or outperform physicians, but the study's own data shows most of the improvement comes from the underlying AI models rather than Microsoft's orchestration layer. The complex cases tested are usually handled by specialists or physician teams, who were not part of the comparison.
MAI-DxO performance and cost data
MAI-DxO works by coordinating several AI agents that act like a panel of doctors. They question a patient, order tests, and debate a diagnosis. Microsoft tested the system with models from OpenAI, Google, Anthropic, Meta, and DeepSeek. Its best results came with OpenAI's GPT-5 and GPT-5.5, released in April 2026.
Microsoft also measured cost, meaning the estimated expense of running the AI on each case. On emergency department cases, there was little difference in accuracy or cost between GPT-5 alone and GPT-5 with DxO. Microsoft researchers said accuracy gains naturally shrink as models approach their theoretical maximum. "The DxO orchestration helps with the broader challenge of optimization both accuracy and cost," a spokesperson said.
- GPT-5 alone: 78.9% accuracy on complex cases at about $8,400 per case. With DxO: cost cut by about $3,000, accuracy up only about four points.
- GPT-5.5 alone: 72% accuracy on complex cases. With DxO: nearly 87% at slightly lower cost.
