Microsoft's AI Diagnostic Orchestrator Beats Generalist Doctors in a Science Study
In a peer-reviewed paper in Science, Microsoft's MAI-DxO system diagnosed simulated cases far more accurately than generalist physicians, though much of the gain appears to come from the underlying OpenAI models.
Key takeaways
- Microsoft's MAI-DxO reached the correct diagnosis in 83.2% of 304 complex NEJM cases and 80.3% of 325 emergency department cases in a study published in Science on October 22, 2026, against 36.1% and 46.8% for generalist physicians.
- The tests ran in a simulated, text-only benchmark built by Microsoft, and the paper says the results do not show the system beats specialists, physician teams or real clinical practice.
- TechCrunch's reading of the study data is that most of the gain comes from stronger underlying models such as GPT-5 and GPT-5.5, with Microsoft's orchestration adding smaller improvements on top.
- Microsoft plans a prospective study with Beth Israel Deaconess Medical Center in Boston in which patients interact with the system directly, and has given no date for a commercial product.
Microsoft on October 22, 2026 published a peer-reviewed study in Science in which its AI diagnostic system, the Microsoft AI Diagnostic Orchestrator (MAI-DxO), reached the correct diagnosis in 83.2% of complex New England Journal of Medicine (NEJM) cases, against 36.1% for generalist physicians who could use reference tools. The tests ran in a simulated, text-only benchmark, and the paper says the results do not establish that the system is better than specialists or real clinical practice.
The paper is the peer-reviewed version of work Microsoft AI first presented as a preprint on June 30, 2025, when it said MAI-DxO paired with OpenAI's o3 solved 85.5% of the same NEJM benchmark cases. Google and OpenAI have made similar claims, TechCrunch notes, as large labs compete to show where AI research in medicine stands against doctors.
What did Microsoft's study in Science find?
MAI-DxO scored 83.2% on 304 NEJM case records and 80.3% on 325 emergency department cases, compared with 36.1% and 46.8% for generalist physicians, according to the paper by Harsha Nori, Eric Horvitz and colleagues published in Science on October 22, 2026. Working without reference tools, the physicians scored 22.3% on the NEJM cases.
The physicians were practicing primary care, hospital and acute care doctors. On 56 NEJM cases held out from development, they gave 764 diagnoses without references and 662 with them. Even the most accurate physician, at 51.8%, was beaten on both accuracy and cost, the paper says.
Microsoft's blog post turns those results into ratios: about 3.7 times and 2.3 times as accurate as physicians on NEJM cases without and with references, and more than 1.7 times on emergency cases. The NEJM cases are clinicopathological conferences, case records chosen for their teaching value, which the paper says may overrepresent hard presentations.
| Diagnostician | Case set | Accuracy | Average cost per case |
|---|---|---|---|
| MAI-DxO, highest accuracy setting | NEJM | 84.5% | $8,945 |
| MAI-DxO, no budget limit | NEJM | 83.2% | $5,431 |
| MAI-DxO, budget limited | NEJM | 80.9% | $2,241 |
| MAI-DxO, tighter budget | NEJM | 79.6% | $1,303 |
| Physicians with references | NEJM | 36.1% | $4,725 |
| Physicians without references | NEJM | 22.3% | $3,049 |
| MAI-DxO, no budget limit | Emergency department | 80.3% | $4,979 |
| MAI-DxO, budget limited | Emergency department | 73.2% | $2,634 |
| MAI-DxO, tighter budget | Emergency department | 69.5% | $2,037 |
| Physicians with references | Emergency department | 46.8% | $3,400 |
How does MAI-DxO reach a diagnosis?
MAI-DxO, called DxO in the paper, turns a language model into a simulated panel of doctors that propose diagnoses, pick questions and tests, and challenge each other over several rounds before committing to an answer, Microsoft says. It weighs the expected value of each test against its cost at every step.
The benchmark, the Sequential Diagnosis Benchmark (SDBench), starts each case with a short vignette. A separate Gatekeeper agent answers only what a real question or test would reveal, and invents neutral results when the record is silent so that missing data does not hint at the answer. A Judge agent grades the final diagnosis on a five-level rubric written by physicians, counting a 4 or 5 as correct. Test costs come from the public price list of Kaiser Permanente Washington's Central Hospital.
The two sides worked differently. Physicians asked a mean of 5.6 questions before ordering their first test, while DxO with GPT-5 asked 25.5, the paper reports.
How much of the gain comes from the orchestrator?
Most of the accuracy appears to come from the underlying model rather than from Microsoft's orchestration layer, TechCrunch concluded from the study's data. GPT-5 alone with a basic prompt scored 78.9% on the NEJM cases at about $8,400 per case, and DxO added about four points while cutting roughly $3,000, TechCrunch reported.
The paper itself says orchestration raised accuracy by an average of 7.9 percentage points on NEJM cases and 4.4 points on emergency cases across all the models tested, which came from OpenAI, Google, Anthropic, Meta and DeepSeek, according to TechCrunch. That average NEJM boost is a small part of the 47 point gap between DxO at 83.2% and physicians with references at 36.1%, a comparison drawn from the paper's numbers rather than one the authors make.
The newer model gives a mixed picture. Microsoft's blog says the gains held up and improved when the evaluation was repeated with GPT-5.5 without changing the method, and the paper says DxO's advantage over the basic prompt grew. On NEJM cases that meant a jump from 72% to nearly 87%, but on emergency cases GPT-5.5 scored about 85% with and without DxO, TechCrunch reported. Weaker models gained more: Gemini 2.5 Flash rose from 46.4% to nearly 69%, according to TechCrunch.
The 2025 preprint put 21 physicians working without references at a mean of 20%, close to the 22.3% now reported; the peer-reviewed paper adds the emergency case set the preprint lacked.
What comes next for MAI-DxO?
Microsoft says it will test the system in a prospective study with Beth Israel Deaconess Medical Center in Boston, in which patients interact with it directly and its performance is measured against physicians' independent assessments. Dominic King, the health lead at Microsoft AI and a coauthor of the paper, told The Verge the study will likely "get underway in the next couple of months."
It needs clinical validation. That is a leap, but this is a major milestone along that journey.
Microsoft has not said when or how the technology might become available, according to The Verge. Suleyman told TechCrunch that Microsoft is working with Mayo Clinic on a health care foundation model it plans to release next year.
For outside researchers, the SDBench code, including the Gatekeeper, Judge and cost estimator, is available under the MIT License. The NEJM based dataset is available from NEJM Group only for noncommercial research under license, and the curated emergency cases are to be released on PhysioNet, the paper says. All authors are Microsoft employees who hold equity in the company, and the paper's competing interests statement also discloses a related Microsoft patent application.
What we don't know yet
- How MAI-DxO compares with specialists or multidisciplinary teams, which the paper says its comparison with individual generalists does not cover.
- How it performs with imaging, waveforms or pathology slides, none of which SDBench includes.
- When the Beth Israel study starts, how many patients it will enroll and when results are due.
- Whether Microsoft will sell MAI-DxO, at what price, and what regulatory clearance it would seek.
- Whether independent groups can reproduce the results on SDBench.
FAQ
What is sequential diagnosis?
Sequential diagnosis is the way doctors work in practice: they start with a short description of the patient, ask questions, order tests one at a time and revise their thinking as results come in. Most AI medical benchmarks instead hand the model the full case at once and ask for one answer. SDBench was built to test the step by step version, including what the tests cost.
Can doctors or patients use MAI-DxO today?
No. MAI-DxO is still a research system, and the Science results come from past cases, not patients. When Microsoft first presented it in June 2025, the company called it a research demonstration that was not approved for clinical use and said it would need safety testing, clinical validation and regulatory review first.
What is MIMIC-IV-ED?
MIMIC-IV-ED is a research database of emergency department visits that is distributed through PhysioNet to credentialed researchers. The Verge describes the cases as drawn from patient admissions at Beth Israel Deaconess Medical Center in Boston. Microsoft says the curated subset it used will be released on PhysioNet.
How does this compare with Google's medical AI work?
Google published a study in The Lancet in October 2026 on its AMIE system in real urgent care visits at Beth Israel, with physicians monitoring in real time, according to TechCrunch. Microsoft's Science results come from simulated cases, and its own real world study with Beth Israel has not started yet.
Sources
- Sequential diagnosis with language models Science · science.org
- Building Medical Superintelligence Microsoft AI · microsoft.ai
- Microsoft's Mustafa Suleyman says its AI outperforms doctors on hard cases as he chases 'medical superintelligence' TechCrunch · techcrunch.com
- Microsoft says its AI tool is better than doctors at diagnosing conditions The Verge · theverge.com
- The Path to Medical Superintelligence Microsoft AI · microsoft.ai
- SDBench source code Microsoft on GitHub · github.com
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