Healthcare AI Insights
Thought leadership on responsible AI deployment, risk stratification, claims automation, and AI governance in healthcare.
Why Explainability Matters More Than Accuracy in Healthcare AI
In healthcare, a model that clinicians understand and trust at 85% accuracy often delivers better outcomes than a black-box model at 95% accuracy.
Risk Stratification
Building Effective Patient Risk Models: Lessons from 50+ Deployments
Key insights on data requirements, feature engineering, and validation strategies for production-ready risk stratification systems.
Compliance
Navigating FDA Regulations for AI-Enabled Medical Devices
A practical guide to understanding when your AI solution requires FDA clearance and how to prepare for the regulatory process.
Claims Automation
Responsible AI for Claims Processing: Balancing Automation and Oversight
How to deploy AI-assisted coding that improves efficiency while maintaining compliance and audit readiness.
Implementation
Moving from AI Pilots to Scaled Healthcare Impact
Why most healthcare AI pilots fail to reach production, and the proven strategies that enable successful scaling.
Data Governance
Establishing AI Governance Frameworks for Healthcare Organizations
Essential components of an effective AI governance program, from oversight committees to ongoing model monitoring.
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