AI outperforms doctors in Harvard trial of emergency triage diagnoses

A groundbreaking Harvard study has found that AI systems outperformed human doctors in high-pressure emergency medicine triage, diagnosing more accurately in the potentially life and death moments when people are first rushed to hospital.

The results were described by independent experts as showing “a genuine step forward” in the clinical reasoning of AIs and came as part of trials that tested the responses of hundreds of doctors against an AI.

The authors said the results, published in the journal Science, showed large language models (LLMs) “have eclipsed most benchmarks of clinical reasoning”.

One experiment focused on 76 patients who arrived at the emergency room of a Boston hospital. An AI and a pair of human doctors were each given the same standard electronic health record to read – typically including vital sign data, demographic information and a few sentences from a nurse about why the patient was there. The AI identified the exact or very close diagnosis in 67% of cases, beating the human doctors, who were right only 50%-55% of the time.

It showed the AIs’ advantage was particularly pronounced in triage circumstances requiring rapid decisions with minimal information. The diagnosis accuracy of the AI – OpenAI’s o1 reasoning model – rose to 82% when more detail was available, compared with the 70-79% accuracy achieved by the expert humans, though this difference was not statistically significant.

But it is not curtains for emergency doctors yet, the researchers said. The study only tested humans against AIs looking at patient data that can be communicated via text. The AI’s reading of signals, such as the patient’s level of distress and their visual appearance, were not tested. That means the AI was performing more like a clinician producing a second opinion based on paperwork.

“I don’t think our findings mean that AI replaces doctors,” said Arjun Manrai, one of the lead authors of the study who heads an AI lab at Harvard Medical School. “I think it does mean that we’re witnessing a really profound change in technology that will reshape medicine.”

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Source: The Guardian, 30 April 2026