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/Prompting Like a Clinician

Prompting Like a Clinician

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The Specificity Principle

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Structured Prompting Templates

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The Five Most Common Prompting Mistakes

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Eliciting Uncertainty

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Ship-Specific Prompting: Lessons from the Edge

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Documenting AI-Assisted Decisions

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Before You Turn the Page

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A Clinician’s Framework for Evaluating AI Tools

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The Regulatory Landscape — What Clinicians Need to Know

In this chapter

Prompting Like a Clinician
The Specificity Principle
Structured Prompting Templates
The Five Most Common Prompting Mistakes
Eliciting Uncertainty
Ship-Specific Prompting: Lessons from the Edge
Documenting AI-Assisted Decisions
Before You Turn the Page