Children need mental health care provided by humans, not chatbots | Letter
Letter: Dr Roman Raczka says artificial intelligence can’t replace therapist-led care, even though it can offer benefits
Health
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Clinical Impact of Artificial Intelligence-Based Triage Systems in Emergency Departments: A Systematic Review
Emergency departments (EDs) worldwide face increasing pressure to optimize triage processes amidst rising patient volumes and resource constraints. Artificial intelligence (AI) has emerged as a potential solution to enhance triage accuracy and efficiency, yet its real-world clinical impact remains inadequately characterized. We conducted a systematic review following Preferred Reporting Items f...
Real-World Impact and Educational Effectiveness of an AI-Powered Medical History-Taking System: Retrospective Propensity Score-Matched Cohort Study
Background Medical history-taking is a core clinical skill; yet, traditional teaching methods face challenges. We developed an artificial intelligence–powered medical history-taking training and evaluation system (AMTES) and established its technical feasibility as an extracurricular resource. Evidence on whether such tools improve learning outcomes when voluntarily embedded in routine curricul...
Both readings
AI now out-diagnoses two expert physicians in triage tests — but saves them almost no time on paperwork
A reasoning model hit 88.6% diagnostic accuracy on clinicopathological cases. In the same window, a five-hospital study found AI scribes returned doctors just 16 minutes per shift. Two headlines, one technology.
Strong gain
Near-physician diagnostic accuracy on complex cases
A reasoning model reached 88.6% exact or near-exact accuracy on clinicopathological cases.
Active harm
Diagnostic bias across underrepresented patient groups
Error rates remain unevenly studied across demographic groups.
Strong gain
Radiology and pathology diagnostic time cut ~90%
In image-heavy specialties with standardized, digitized data, AI has reduced diagnostic time dramatically.