A practical framework for aligning clinicians, IT, and operations on a single healthcare AI initiative—covering scope, governance, validation, integration readiness, and change management through go-live and scaling.
Identify and mitigate three silent AI risks in healthcare digital systems—bias, adversarial security threats, and systemic harms—with a practical governance, auditing, monitoring, and incident-response playbook.
A practical framework for aligning clinicians, IT, and operations on a single healthcare AI initiative—covering scope, governance, validation, integration readiness, and change management through go-live and scaling.
Identify and mitigate three silent AI risks in healthcare digital systems—bias, adversarial security threats, and systemic harms—with a practical governance, auditing, monitoring, and incident-response playbook.
A four-phase SafeOps framework for running an AI pilot in healthcare—covering evaluation, algorithmic validation, real-workflow testing, and continuous monitoring with clear ownership across business, data science, operations, and compliance.
A four-phase SafeOps framework for running an AI pilot in healthcare—covering evaluation, algorithmic validation, real-workflow testing, and continuous monitoring with clear ownership across business, data science, operations, and compliance.
A practical framework for discussing AI initiatives with a healthcare board: define business problems, set measurable KPIs and ROI ranges, communicate risks and mitigations, and use governance plus staged pilots to avoid hype-driven decisions.
A practical framework for discussing AI initiatives with a healthcare board: define business problems, set measurable KPIs and ROI ranges, communicate risks and mitigations, and use governance plus staged pilots to avoid hype-driven decisions.