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Dan Noyes - Medical AI Perspectives

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Dan Noyes

Dan Noyes

The Patient's AI Bill of Rights: Part 4 - A Hospital AI Implementation Framework

The Patient's AI Bill of Rights: Part 4 - A Hospital AI Implementation Framework

Bringing Beneficence, Respect for Persons, and Justice Together in Practice Why share? With so many voices clamouring for our attention with all things AI, I must first state that my voice is that of a patient who lived through a sentinel event. I have seen how AI could have prevented

My Sentinel Event

My Sentinel Event

Leveraging Artificial Intelligence to Proactively Reduce Medical Sentinel Events Executive Summary This is personal. I had a life-altering sentinel event that haunts me to this day. The neurologist made a mistake. A big mistake. He overprescribed a medication by nearly 200 times the recommended dosage. I am fortunate to be

Justice in a Patient Bill of Rights

Justice in a Patient Bill of Rights

Justice in healthcare AI demands that we actively design systems to close, not widen, existing health disparities. This means confronting algorithmic bias head-on, ensuring diverse representation in data and development teams, and implementing robust equity frameworks throughout the AI lifecycle.

Research Paper: Laying the Foundation for a Patient's AI Bill of Rights

Research Paper: Laying the Foundation for a Patient's AI Bill of Rights

The concepts of creating a patient's bill of rights, including a respect for persons, beneficence, and justice, as outlined in the Belmont Report.

Confronting Bias, Safety, and Governance in Healthcare AI

Confronting Bias, Safety, and Governance in Healthcare AI

Best practices in confronting data bias, system safety, and data governance in your medical AI solutions.

The Promise and Reality of AI in Global Health

The Promise and Reality of AI in Global Health

AI represents a critical opportunity to address one of the most pressing moral challenges of our time: the fact that 4.5 billion people—nearly half of humanity—lack access to essential healthcare services.

Healthcare AI Validation: The Critical Gap in Post-Market Monitoring

Healthcare AI Validation: The Critical Gap in Post-Market Monitoring

Despite rapid adoption, a significant majority of AI models (81%) experience performance degradation when deployed in external datasets, with nearly a quarter (24%) showing substantial decreases and 12% experiencing complete failure.