Diagnosis: critical deficit in clinical readiness

Based on this article by Rajan Kohli posted on Forbes.

Generic AI platforms often fail in healthcare because they are fundamentally incompatible with the industry's high-stakes and complex realities, leading to a critical "illusion of readiness." Healthcare data is uniquely varied, ranging from unstructured clinical notes to images, and success requires the AI to navigate maze-like workflows of patient care, not just benchmark well.

Given that an error can cost a life, traceability, explainability, and policy alignment are non-negotiable ethical and regulatory prerequisites that general models cannot reliably guarantee. Moving forward requires a pivot toward domain-native platforms built with clinical literacy and compliance engineered at their core to earn clinician trust and safely scale.

Check out this article.

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