As the rush toward AI in healthcare continues, explainability is crucial
Healthcare IT News
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Contributed by: Drex DeFord
Summary
As interest in AI grows within healthcare, its implementation has shown success predominantly in administrative tasks with fewer clinical applications due to concerns about model transparency and explainability. Neeraj Mainkar, a software engineering expert at Proprio, discusses the critical need for understanding AI decision-making processes in the healthcare sector to ensure patient safety and foster trust. Explainable AI is necessary to trace decision paths, identify and rectify errors, mitigate bias, maintain regulatory compliance, and uphold ethical standards. This approach ensures AI systems are transparent, reliable, and compliant with healthcare regulations like HIPAA, thereby promoting fair and effective patient care.
