British tech pioneer Mustafa Suleyman<\/a>, has developed a system that imitates a panel of expert physicians tackling \u201cdiagnostically complex and intellectually demanding\u201d cases.<\/p>\nMicrosoft said that when paired with OpenAI\u2019s advanced o3 AI model, its approach \u201csolved\u201d more than eight of 10 case studies specially chosen for the diagnostic challenge. When those case studies were tried on practising physicians \u2013 who had no access to colleagues, textbooks or chatbots \u2013 the accuracy rate was two out of 10.<\/p>\n
Microsoft said it was also a cheaper option than using human doctors because it was more efficient at ordering tests.<\/p>\n
Despite highlighting the potential cost savings from its research, Microsoft played down the job implications, saying it believed AI would complement doctors\u2019 roles rather than replace them.<\/p>\n
\u201cTheir clinical roles are much broader than simply making a diagnosis. They need to navigate ambiguity and build trust with patients and their families in a way that AI isn\u2019t set up to do,\u201d the company wrote in a blogpost announcing the research, which is being submitted for peer review.<\/p>\n
However, using the slogan \u201cpath to medical superintelligence\u201d raises the prospect of radical change in the healthcare market. While artificial general intelligence (AGI) refers to systems that match human cognitive abilities at any given task, superintelligence is an equally theoretical term referring to a system that exceeds human intellectual performance across the board.<\/p>\n
Explaining the rationale behind the research, Microsoft raised doubt over AI\u2019s ability to score exceptionally well in the United States Medical Licensing Examination, a key test for obtaining a medical licence in the US. It said the multiple-choice tests favoured memorising answers over deep understanding of a subject, which could help \u201coverstate\u201d the competence of an AI model.<\/p>\n
Microsoft said it was developing a system that, like a real-world clinician, takes step-by-step measures \u2013 such as asking specific questions and requesting diagnostic tests \u2013 to arrive at a final diagnosis. For instance, a patient with symptoms of a cough and fever may require blood tests and a chest X-ray before the doctor arrives at a diagnosis of pneumonia.<\/p>\n
The new Microsoft approach uses complex case studies from the New England Journal of Medicine (NEJM).<\/p>\n
Suleyman\u2019s team transformed more than 300 of these studies into \u201cinteractive case challenges\u201d that it used to test its approach. Microsoft\u2019s approach used existing AI models, including those produced by ChatGPT\u2019s developer, OpenAI, Mark Zuckerberg\u2019s Meta, Anthropic, Elon Musk\u2019s Grok and Google\u2019s Gemini.<\/p>\n
Microsoft then used a bespoke, agent-like AI system called a \u201cdiagnostic orchestrator\u201d to work with a given model on what tests to order and what the diagnosis might be. The orchestrator in effect imitates a panel of physicians, which then comes up with the diagnosis.<\/p>\n
Microsoft said that when paired with OpenAI\u2019s advanced o3 model, it \u201csolved\u201d more than eight of 10 NEJM case studies \u2013 compared with a two out of 10 success rate for human doctors.<\/p>\n
Microsoft said its approach was able to wield a \u201cbreadth and depth of expertise\u201d that went beyond individual physicians because it could span multiple medical disciplines.<\/p>\n
It added: \u201cScaling this level of reasoning \u2013 and beyond \u2013 has the potential to reshape healthcare. AI could empower patients to self-manage routine aspects of care and equip clinicians with advanced decision support for complex cases.\u201d<\/p>\n
Microsoft acknowledged its work is not ready for clinical use. Further testing is needed on its \u201corchestrator\u201d to assess its performance on more common symptoms, for instance.<\/p>\n","protected":false},"excerpt":{"rendered":"Microsoft has revealed details of an artificial intelligence system that performs better than human doctors at complex health…\n","protected":false},"author":2,"featured_media":227379,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3163],"tags":[323,1942,53,16,15],"class_list":{"0":"post-227378","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-technology","11":"tag-uk","12":"tag-united-kingdom"},"share_on_mastodon":{"url":"","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/posts\/227378","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/comments?post=227378"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/posts\/227378\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/media\/227379"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/media?parent=227378"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/categories?post=227378"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/uk\/wp-json\/wp\/v2\/tags?post=227378"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}