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Study Finds AI Outshines Doctors

Coughs, sore throats, urinary tract infections, and eye problems could one day be diagnosed not by a human doctor, but by artificial intelligence (AI), according to new research. A recent study published in the Annals of Internal Medicine found that AI systems may actually outperform physicians in certain urgent care scenarios.

The study involved comparing the clinical decisions of an AI tool to those of human doctors across 461 real patient visits involving common acute symptoms such as respiratory infections, eye irritation, and dental or urinary complaints. The AI system matched doctors’ diagnoses and treatment plans in roughly two-thirds of the cases. However, in the remaining third where the recommendations differed, AI was judged to offer the better course of action twice as often as the doctors.

Researchers noted that the AI system, trained on a vast database of medical cases and real-world data, was more likely to follow established clinical guidelines strictly. This may have contributed to its superior performance in many cases. Additionally, AI recommendations were rated as less likely to be harmful compared to those made by human practitioners. The system also showed a high level of caution, refraining from giving recommendations in about 20% of cases when it lacked confidence.

Despite the promising results, researchers emphasized that AI should be used as a supportive tool rather than a replacement for human judgment. While the AI demonstrated strong potential as a second opinion resource, human doctors maintain an edge in their ability to ask clarifying questions and adapt to complex, nuanced situations during patient interactions.

In an editorial accompanying the study, Dr. Jerome Kassirer of Tufts University suggested that clinicians use AI as a backup to confirm their own diagnoses and treatment choices. He stressed the importance of understanding how an AI system works, its track record, and any potential biases it may carry. Exploring discrepancies between AI and human diagnoses, he added, could help further refine these emerging tools.