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Clinical AI
AI at the point of care: diagnostics, clinical decision support, ambient documentation, and the hospital workflows where models meet patients and clinicians. What actually changes practice versus what stays a demo.
These essays cut through the binary of "AI will replace doctors" versus "AI is useless at the bedside" to ask where clinical AI actually works and what it takes to trust it. The throughline: the technology is rarely the bottleneck — clinical inertia, broken systems, missing benchmarks, and the gap between a great product and a viable business are. The real shift is from answers to actions, with data standards and neutral, task-specific evaluation mattering more, and augmenting clinicians beating replacing them.