AI Diagnosis: Microsoft Claims 83% Accuracy Rate

83% versus 36%. That's the stark gap in diagnostic accuracy on a set of complex medical cases between Microsoft's new AI system and human generalist physicians working individually. The results, published in the journal Science on October 22, show the company's tool, MAI-DxO, is more than twice as effective at reaching the correct conclusion in these difficult scenarios. Mustafa Suleyman, the CEO of Microsoft AI, called the outcome a significant step toward a goal he terms "medical superintelligence."

The system, referred to as DxO, functions by deploying a coordinated panel of AI agents that interact with a patient, request tests, and then debate potential diagnoses. In a simulation using difficult cases from the New England Journal of Medicine, it achieved its high accuracy mark. By comparison, primary care doctors and general internists, who had access to reference materials, were correct just 36% of the time. The source material did note that cases of this complexity are typically handled by specialists or physician teams, who were not part of this comparison.

The study also provides a look at the cost implications of using such technology. Running GPT-5 on its own with a simple prompt to answer a complex case costs an estimated $8,400 per case with an accuracy of 78.9%. Microsoft's DxO system reduced that cost by about $3,000, but the accuracy only rose by roughly four points. On emergency department cases, there was little improvement in either accuracy or cost when comparing GPT-5 with and without DxO's assistance.

The results varied significantly when using different AI models. With GPT-5.5, a model released in April 2026, DxO increased accuracy on complex cases from 72% to nearly 87% at a slightly lower cost. However, for emergency department cases, both configurations scored around 85% at a similar cost. Microsoft's own analysis suggests that accuracy gains naturally diminish as models approach a theoretical maximum, with a company spokesperson stating that "The DxO orchestration helps with the broader challenge of optimization both accuracy and cost."

The publication of this study aligns with Microsoft's stated goal of creating systems that can surpass human-led health systems in medical reasoning. Suleyman, who previously co-founded DeepMind, said that Microsoft is working with the Mayo Clinic to train a foundation model for healthcare, with a release planned for next year. He believes this model will enable the company to "make really enormous leaps here." He also said, "I really believe that in 2027, we will be on the verge of a coding style breakthrough for medical records."

To evaluate the technology further, Microsoft is partnering with Beth Israel Deaconess Medical Center in Boston to assess DxO's clinical reasoning capabilities in a real-world setting. Patients will receive standard care, while consenting participants will also engage with DxO. Microsoft and its partners will then compare the AI's recommendations against those of the human doctors. Dominic King, vice president of Health at Microsoft AI, stated, "We think this will be the biggest study of its kind."