Chatbots are a reliable first stop for early symptom checks and can catch illness in its early stages.
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Expert: Arya Rao (lead author, JAMA Network Open study), Researcher, Mass General Brigham The claim that AI chatbots are a reliable first stop for early symptom checks is contradicted by new peer-reviewed research. A JAMA Network Open study (“Large Language Model Performance and Clinical Reasoning Tasks”) tested 21 large language models — including GPT-4, Gemini, Grok and Claude — across 29 clinical case scenarios, generating 16,254 diagnostic responses. Key findings: • Models misdiagnosed more than 80% of early-stage cases, when symptoms are often non-specific. • Even when the correct diagnosis appeared in the output, it was frequently not ranked as the most likely option, reducing its practical value. • Failure rates fell below 40% once full clinical data was provided, with the best-performing models exceeding 90% accuracy. “These models are great at naming a final diagnosis once the data is complete, but they struggle at the open-ended start of a case, when there isn’t much information,” said the study’s lead author, Arya Rao, a researcher at Mass General Brigham. The finding inverts the claim: early-stage symptom checks — precisely the moment when timely intervention matters most — are the least reliable use of AI. Unlike doctors, the models do not reason clinically; they predict patterns from vast datasets, cannot ask meaningful follow-up questions, and cannot reassess conclusions dynamically. Chatbots may support general awareness and help patients structure conversations with doctors, but they should not be relied upon for diagnosis or treatment decisions. Source: https://www.business-standard.com/health/ai-chatbots-misdiagnose-early-cases-80-percent-study-126041400329_1.html
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