Fortune | FORTUNE 19小时前
Microsoft claims its AI tool can diagnose complex medical cases four times more accurately than doctors
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微软发布了一款名为MAI-DxO的AI诊断工具,该工具在诊断准确性上超越了医生。MAI-DxO通过模拟医生团队,利用标准医学执照考试数据进行训练,在处理超过300个真实案例时,准确率达到85%。微软认为,这款AI工具能够以更具成本效益的方式做出诊断,并结合了广泛和深入的专业知识。尽管AI在医疗保健领域发展迅速,但仍面临信任、数据安全和医生角色等方面的挑战。微软强调,AI是医生的补充,无法取代医生在构建人际关系和理解患者需求方面的作用。

🩺 微软的MAI-DxO AI诊断工具在诊断准确性上优于医生,尤其是在处理复杂案例时,诊断准确率达到85%。

💡 MAI-DxO通过模拟医生团队,并使用标准医学执照考试数据进行训练,能够结合广泛和深入的专业知识,以更具成本效益的方式做出诊断。

🤔 尽管AI在医疗保健领域发展迅速,但仍面临挑战,包括如何实施、敏感数据积累以及医生未来的角色。研究表明,近一半的美国患者和63%的临床医生对AI改善健康结果持乐观态度。

🤝 微软强调,AI是医生的补充,而非替代。医生在处理不确定性和与患者建立信任方面具有独特优势,而AI无法复制这种能力。

One of the world’s global powerhouses announced what could be a big win for the AI economy. 

In a blog post, Microsoft said its AI diagnostic tool—the Microsoft AI Diagnostic Orchestrator (MAI-DxO), which simulates a panel of physicians and is trained using the standard Medical Licensing Examination—diagnosed cases four times as accurately as physicians after both parties were able to ask questions, order tests, and, eventually, finalize a diagnosis. 

In the post—written by Harsha Nori, head of AI at Microsoft AI Health, and Dominic King, VP of Health at Microsoft AI—the company claimed its AI diagnosed 85% of over 300 real-world cases correctly, and that the model’s process “gets to the correct diagnosis more cost-effectively than physicians.”

Microsoft claims MAI-DxO “can blend both breadth and depth of expertise, demonstrating clinical reasoning capabilities that, across many aspects of clinical reasoning, exceed those of any individual physician.” 

The rise of Dr. AI

AI is already rapidly evolving across the health care ecosystem. According to Microsoft, over 50 million health-related sessions occur daily using Microsoft’s AI consumer products. “From a first-time knee-pain query to a late-night search for an urgent-care clinic, search engines and AI companions are quickly becoming the new front line in healthcare,” the blog post said. 

Beyond being a sounding board for health questions, AI is also expanding into physical clinics. With staffing shortages, long wait times, and a total of $5 trillion in annual health care expenditures, the industry is ripe for technological advancements. 

In diagnostics, a separate study found couples in distress can derive similar mental-health benefits from AI therapy as they can from human therapists. However, there is still hesitancy about how the AI will be implemented, the accumulation of sensitive data, and, of course, the future of the doctor. 

Nearly half of U.S. patients (48%) and 63% of clinicians are optimistic that AI can improve health outcomes, according to research from the 2025 Philips Future Health Index (FHI). It’s undeniable that minding this gap and building optimism among consumers, particularly those who may not trust traditional health care, is key to building and scaling new technological solutions. 

“Breakthroughs need trust for real-world impact,” Dominic King, who co-wrote the blog post, told Fortune in a statement. “That’s why we’re committed to earning the trust of health care professionals and patients through rigorous safety testing, clinical validation, and regulatory reviews.”

Microsoft said it views the technology as a “complement to doctors and other health professionals” and emphasized doctors’ ability “to navigate ambiguity and build trust with patients and their families” is not something AI can replicate.

“Doctors aren’t going anywhere. AI will help them arrive at diagnoses and effective care plans faster, but it can’t replace the human connection and understanding patients’ needs,” King said. 

The team at Microsoft noted the limitations of this research. For one, the physicians in the study had between five and 20 years of experience, but were unable to use textbooks, coworkers, or—ironically—generative AI for their answers. It could have limited their performance, as these resources may typically be available during a complex medical situation. Moreover, the doctors and AI analyzed only complex cases and not everyday ones. 

“Important challenges remain before generative AI can be safely and responsibly deployed across healthcare,” the team wrote. “We need evidence drawn from real clinical environments, alongside appropriate governance and regulatory frameworks to ensure reliability, safety, and efficacy.”

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微软 AI诊断 医疗保健 人工智能
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