AI Literacy for Clinicians: What Every Physician Needs to Know Before Trusting the Algorithm

Javier Rosas

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Table of Contents

AI Literacy for Clinicians: What Every Physician Needs to Know Before Trusting the Algorithm

What Happens When You Talk to AI
Why AI Sounds Confident But Gets It Wrong
Where the Training Data Came From (And Why That Matters)
The Six-Platform Study — What I Found When I Tested Clinical AI
When AI Assumes Resources You Don’t Have
The Failure Modes That Matter Most
A Clinician’s Framework for Evaluating AI Tools
Prompting Like a Clinician
The Regulatory Landscape — What Clinicians Need to Know
The Future of Clinical AI — From the Edge of Medicine
Appendix A: Glossary of AI Terms for Clinicians
Appendix B: AI Evaluation Checklist for Clinicians
- Regulatory Status Quick Check
- Documentation Template
Appendix C: Prompting Templates for Common Clinical Scenarios

AI Literacy for Clinicians: What Every Physician Needs to Know Before Trusting the Algorithm/Appendix A: Glossary of AI Terms for Clinicians

Appendix A: Glossary of AI Terms for Clinicians

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How the Models Work

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Training and Alignment

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Errors and Failure Modes

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Architecture and Safety

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Regulation and Governance

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Evaluation and Benchmarks

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The Future of Clinical AI — From the Edge of Medicine

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Appendix B: AI Evaluation Checklist for Clinicians

In this chapter

Appendix A: Glossary of AI Terms for Clinicians
How the Models Work
Training and Alignment
Errors and Failure Modes
Architecture and Safety
Regulation and Governance
Evaluation and Benchmarks