AI Diagnostics: Microsoft Claims Higher Accuracy Than Human Doctors

Microsoft is accelerating its push into the healthcare sector with the release of a new AI diagnostic tool, claiming significant advancements in medical reasoning capabilities.

According to a study published today in the journal Science, Microsoft's AI diagnostic system, named MAI-DxO, correctly identified complex medical cases at a rate of 83%. This figure more than doubles the 36% accuracy rate achieved by primary care doctors and general internists operating individually with reference materials during a simulation involving cases from the New England Journal of Medicine. It is important to note that cases of this complexity are typically managed by specialists or medical teams, who were not included in this specific comparison.

The MAI-DxO system functions by orchestrating multiple AI agents to simulate a panel of medical professionals. These agents work by questioning a patient, ordering tests, and debating potential diagnoses to arrive at a conclusion. Mustafa Suleyman, the CEO of Microsoft AI, characterized this result as a step toward developing medical superintelligence, a capability defined in a Microsoft manifesto as surpassing human-led health systems in medical reasoning and coordination.

The study indicates that a substantial portion of the improvement stems from advancements in underlying AI models, though the DxO orchestration system provides additional gains. Microsoft tested the system with models from various providers, including OpenAI, Google, Anthropic, Meta, and DeepSeek, but achieved its highest accuracy rates using OpenAI's GPT-5 and GPT-5.5. For instance, on complex cases, DxO increased GPT-5.5's accuracy from 72% to nearly 87% at a slightly reduced cost.

The effectiveness of the orchestration layer varies depending on the task and the underlying model. On emergency department cases, little improvement in accuracy or cost was observed when comparing GPT-5 to GPT-5 with DxO. Furthermore, while DxO assists less capable models, such as Gemini 2.5 Flash which rose from 46.4% to nearly 69% accuracy, the gap between weaker and stronger models remained larger than the boost provided by DxO.

Mustafa Suleyman stated that Microsoft is collaborating with the Mayo Clinic to train a foundation model for healthcare, with a release planned for next year. Suleyman, who previously co-founded DeepMind, expects healthcare models to improve by an order of magnitude in capability within the next 24 to 36 months. He expressed confidence in a coding-style breakthrough for medical records in 2027, enabling the streaming of highly accurate predictions about how a medical record might unfold.

To evaluate real-world performance, Microsoft has entered a partnership with Beth Israel Deaconess Medical Center in Boston to assess the clinical reasoning capabilities of DxO across various hospital settings. Patients will receive standard care, while consenting participants will also engage with DxO, allowing Microsoft and its partners to compare recommendations against those of human doctors. Dominic King, vice president of Health at Microsoft AI, stated, "We think this will be the biggest study of its kind."