{"id":891768,"date":"2026-10-23T08:40:22","date_gmt":"2026-10-23T08:40:22","guid":{"rendered":"https:\/\/www.newsbeep.com\/us\/891768\/"},"modified":"2026-10-23T08:40:22","modified_gmt":"2026-10-23T08:40:22","slug":"microsofts-mustafa-suleyman-says-its-ai-outperforms-doctors-on-hard-cases-as-he-chases-medical-superintelligence","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us\/891768\/","title":{"rendered":"Microsoft\u2019s Mustafa Suleyman says its AI outperforms doctors on hard cases as he chases \u2018medical superintelligence\u2019"},"content":{"rendered":"

Microsoft\u2019s AI diagnostic system correctly diagnosed complex medical cases in a simulation more than twice as often as generalist physicians, according to a study published Thursday<\/a> in Science. Mustafa Suleyman, Microsoft AI\u2019s CEO, called the result a step toward \u201cmedical superintelligence.\u201d<\/p>\n

The system, dubbed MAI-DxO (DxO for short), coordinates several AI agents that act like a panel of doctors. They question a patient, order tests, and debate a diagnosis.<\/p>\n

In a simulation using complex cases from the New England Journal of Medicine, it was correct 83% of the time. Primary care doctors and general internists, working individually with reference materials, were correct 36% of the time. One note: Cases this complex are usually handled by specialists or physician teams, who weren\u2019t part of the comparison.<\/p>\n

\u201cThere is something very substantial and exciting here,\u201d Dominic King, vice president of Health at Microsoft AI, told TechCrunch. \u201cThe biggest challenge in healthcare delivery at the moment is the growing mismatch between demand and supply of medical expertise.\u201d<\/p>\n

In publishing these results<\/a>, Microsoft joins Go<\/a>o<\/a>gle<\/a> and OpenAI<\/a> in claiming that its AI can match or outperform doctors.<\/p>\n

The study\u2019s own data suggests that much of the improvement comes from more powerful underlying AI models, with Microsoft\u2019s orchestration system adding gains on top.<\/p>\n

Microsoft tested MAI-DxO with models from several companies, including OpenAI, Google, Anthropic, Meta, and DeepSeek, but its best results came with OpenAI\u2019s GPT-5 and GPT-5.5.\u00a0<\/p>\n

\"\"Accuracy improvements delivered by DxO (no budget constraints) on CPC over models
prompted with baseline prompt across different large language models.Image Credits:Microsoft AI<\/p>\n

Microsoft measured DxO on cost as well as accuracy, meaning the estimated cost of running the AI on each case. On its own with a short, basic prompt, GPT-5 scored 78.9% on complex cases at about $8,400 per case. DxO cut that cost by about $3,000 but raised accuracy by only about four points. On emergency department cases, there was little improvement in either accuracy or cost improvement between GPT-5 on its own and with the assist from DxO.<\/p>\n

With GPT-5.5, a newer model released in April 2026, the results split. On complex cases, DxO increased GPT-5.5\u2019s accuracy score from 72% to nearly 87% at a slightly cheaper cost. However, the gains once again didn\u2019t show up on emergency department cases. Both (with and without DxO) scored about 85% at a similar cost.\u00a0<\/p>\n

DxO helps most on complex cases and with less capable AI models. Gemini 2.5 Flash, for example, scored 46.4% on its own but nearly 69% with DxO. Even so, the gap between the weaker and stronger models was larger than the boost DxO provided.<\/p>\n

Microsoft\u2019s researchers said that accuracy gains naturally shrink as models approach the theoretical maximum. \u201cThe DxO orchestration helps with the broader challenge of optimization both accuracy and cost,\u201d a spokesperson added.<\/p>\n

Suleyman, who leads Microsoft\u2019s effort to build its own frontier AI, told TechCrunch that the company is working with the Mayo Clinic to train a foundation model for healthcare, with release planned for next year. He believes this model will enable the company to \u201cmake really enormous leaps here,\u201d and says DxO is part of the foundational infrastructure Microsoft is building to see real breakthroughs in healthcare.\u00a0<\/p>\n

\u201cI really believe that in 2027, we will be on the verge of a coding style breakthrough for medical records,\u201d Suleyman said. \u201cI think we\u2019re going to be able to stream highly accurate predictions about how a medical record might unfold, and obviously that kind of foresight for a clinician is gold dust.\u201d<\/p>\n

Suleyman has spent his career trying to use AI to solve medical issues. He was previously a co-founder of DeepMind, which was acquired by Google in 2014. The following year, Google DeepMind acquired King\u2019s startup Hark, a clinical task management app, and the two of them launched DeepMind Health together. Suleyman joined Microsoft to lead its AI unit in 2024, and King followed a few months later.<\/p>\n

\u201cWe\u2019re just true believers,\u201d Suleyman said.<\/p>\n

He said while the use of generative AI in healthcare is still early, he expects healthcare models to get \u201can order of magnitude better in capability within the next 24 to 36 months.\u201d\u00a0<\/p>\n

\u201cAs we\u2019ve seen multiple times in the last five or six years, the progress happens very quickly once you have a flywheel,\u201d Suleyman said. \u201cA flywheel means we have a model in production which we are iterating with real-world usage in order to identify gaps in the model and then patch them and improve them. That\u2019s what\u2019s happened in coding. It\u2019s what happened in chat before that. And I think next year it\u2019s going to start to happen for medical records and for clinical decision support.\u201d<\/p>\n

Through a new partnership with Beth Israel Deaconess Medical Center in Boston, Microsoft will evaluate the clinical reasoning capabilities of DxO across different hospital settings.<\/p>\n

\u201cThis technology is ready for real-world evaluations, and you can imagine the complexity and diversity of issues that come from a Boston emergency department on a Friday evening,\u201d King said.<\/p>\n

He explained how the study will work: Patients will get standard treatment, including triage, time with a specialist, treatments, investigations, and decision on whether it\u2019s safe to discharge. In parallel, those who consent will also engage with DxO. Microsoft and its partners will compare DxO\u2019s recommendations against the human doctors\u2019.\u00a0<\/p>\n

Google published<\/a> a clinical study alongside Beth Israel in The Lancet this month to evaluate Google\u2019s AMIE conversational diagnostic AI in real-world urgent care visits, while human physicians monitored the interactions in real time.\u00a0<\/p>\n

\u201cWe think this will be the biggest study of its kind,\u201d King said. \u201cIt will be across not just emergency settings but urgent care environments, and will give us very compelling evidence by the end of the\u00a0study period around the ability for these systems to be deployed at greater scale in the future.\u201d<\/p>\n

Microsoft\u2019s study in Science coincides with a manifesto of sorts around what it will take to build medical superintelligence, defined as \u201cthe capacity to surpass the strongest contemporary human-led health systems in medical reasoning and coordination across the full arc of care.\u201d Microsoft hopes to move beyond benchmarking individual tasks \u2014 like answering medical exam questions and generating diagnoses \u2014 into integrating with clinicians and healthcare systems for better outcomes.\u00a0<\/p>\n

\u201cThis is the kind of technology that everybody in the world wants, and that\u2019s why we\u2019re committed to doing everything we can to accelerate its introduction to the world,\u201d Suleyman said, adding that this focus could be a differentiator for Microsoft compared to the other frontier labs.\u00a0<\/p>\n

Microsoft already sells dictation and radiology tools to clinicians and sees DxO as an expansion to those efforts.\u00a0<\/p>\n

\u201cWe have to have the absolute number one state-of-the-art medical clinical decision support products over the next few years,\u201d Suleyman said.\u00a0<\/p>\n

When you purchase through links in our articles, we may earn a small commission<\/a>. This doesn\u2019t affect our editorial independence.<\/p>\n","protected":false},"excerpt":{"rendered":"Microsoft\u2019s AI diagnostic system correctly diagnosed complex medical cases in a simulation more than twice as often as…\n","protected":false},"author":2,"featured_media":891769,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[45],"tags":[182,181,507,26130,67252,74],"class_list":["post-891768","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-microsoft-ai","tag-mustafa-suleyman","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/891768","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/comments?post=891768"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/891768\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media\/891769"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media?parent=891768"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/categories?post=891768"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/tags?post=891768"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}