Themes
The book's chapters grouped into 8 themes.
Foundations of AI in Healthcare
What artificial intelligence in healthcare actually is, and why judging it by its function rather than its label is the first step.
Data and Interoperability
Health records, HL7 FHIR and vendor lock-in: why AI can only see the patient that the data allows it to see.
Clinical AI: Diagnosis and Prediction
Radiology, predictive medicine and personalized medicine: where AI already changes practice every day.
The Physician and the Time for Care
Information overload, ambient listening and documentation: how to give attention back to the clinical encounter.
Hospital Management and Operations
Operating rooms, supply chain, billing and telemedicine: the AI that never shows up on the CT scan.
Ethics, Bias and Accountability
Algorithmic bias, explainability and the unavoidable question: who answers when AI gets it wrong?
Security and Trust
Cybersecurity, adoption culture and the role of the physician "champion" in trusting new technology.
The Future of Care
The ROI of AI in healthcare and a speculative portrait of the hospital in 2035.