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Microsoft researchers said in a study that a new artificial intelligence (AI) tool that can diagnose patients step by step, as a doctor would, was more than twice as accurate as general practitioners in solving complex medical cases.
The study, published Thursday in Science, indicates that the AI model takes a different approach to diagnosing medical problems than most other models that seek to solve these problems.
Microsoft said the AI model identifies and coordinates the questions that should be asked of a patient as well as the exams and tests that should be ordered using an “orchestrator” that organizes how the AI will approach a problem by employing a simulated panel of clinical experts collaborating to solve diagnostic cases, the report said.
In contrast, existing AI models typically take a holistic approach that looks at all of a patient’s symptoms, lab results, and imaging studies to generate a diagnosis.
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Microsoft’s research showed that the AI orchestrator was more effective in diagnosing complex cases at a lower cost. (Nvidia)
While the orchestrator coordinates the steps to reach a diagnosis, the AI model first decides what questions to ask about the patient’s medical history and identifies important findings from the physical exam.
Based on the lessons learned from this process, it decides which tests to order, reviews the results, and orders additional tests as appropriate. As these tasks continue, the AI model updates its assumptions and work plans.
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Microsoft will then test the AI model and orchestrator in an emergency room. (Philips)
The tool also outperformed human doctors when presented with scenarios drawn from a large emergency room admissions database. The researchers said assessments comparing these types of older systems to human doctors typically use multiple-choice questions.
“AI has become very good at achieving a 100% success rate,” said Dr. Dominic King, vice president of Microsoft’s healthcare unit AI, which is developing the new technology. “But, of course, that’s not the real world. No patient has ever come to me with a pretty summary.”
The researchers tasked the model with diagnosing more than 300 highly unusual and confusing medical dilemmas and found that the model using the Diagnostic Orchestrator was more than twice as accurate in “assessing” the patient and determining the diagnosis than general practitioners using textbooks and the Internet.
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Researchers also found that diagnostic processes cost less when the orchestrator designs the assessments than when doctors do so.
“We don’t just measure the accuracy of systems. We also measure how wisely and thoroughly a diagnosis is made,” said Harsha Nori, head of AI at Microsoft AI Health.
The Microsoft research team’s next test will take place in a collaboration with Beth Israel Deaconess Medical Center in Boston, where it will evaluate the tool’s ability to triage patients in emergency department waiting rooms.
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Reuters contributed to this report.
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