AI in Healthcare Proficiency Quiz
For Healthcare Professionals
Test your understanding of AI's role in clinical practice — from diagnostic algorithms and EHR AI to regulatory approval, algorithmic bias, and the ethical dimensions of AI-assisted care. 20 questions for clinicians, administrators, and health informatics professionals.
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20 questions · 15–20 minutes · Intermediate
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👤 Who is this for?
Designed for physicians, nurses, pharmacists, radiologists, health informatics professionals, healthcare administrators, and clinical researchers who want to understand AI's role in healthcare. No programming background required.
💡 Why AI literacy matters
AI is entering clinical workflows at speed — from diagnostic imaging and early warning systems to EHR summarization and drug discovery. Healthcare professionals who understand AI's capabilities, limitations, and risks are better equipped to use it safely, challenge it appropriately, and protect their patients.
Topics Covered in This Assessment
Frequently Asked Questions
What AI knowledge do healthcare professionals need in 2025?
Healthcare professionals should understand what AI can and cannot do clinically, how to critically appraise AI study evidence, how AI diagnostic tools are regulated (FDA, CE marking), the risks of algorithmic bias across patient populations, how to maintain meaningful human oversight of AI recommendations, and the ethical and legal implications of AI-assisted clinical decisions.
Is AI replacing doctors and nurses?
The current evidence suggests AI augments rather than replaces clinical professionals. AI excels at specific pattern recognition tasks (radiology image reading, ECG interpretation, pathology) but lacks the holistic reasoning, contextual judgment, communication, and ethical decision-making that defines clinical care. The consensus model is AI as a powerful tool under clinician oversight.
How are AI medical devices regulated?
In the US, the FDA regulates AI/ML-based medical devices under its Software as a Medical Device (SaMD) framework. AI tools used for clinical diagnosis or treatment decisions typically require 510(k) clearance or De Novo authorization. The FDA has also issued guidance on AI/ML action plans for continuously learning systems. In the EU, the Medical Device Regulation (MDR) and AI Act apply.
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Simone Banks created an AI app to parse payment info from invoices.
Marcus Chen built an agent to summarize meeting notes from documents.
Elena Rodriguez made an app to extract customer feedback from Excel files.
James Mitchell created an agent to analyze competitor pricing from web links.
Pritika Rajan built an AI app to generate weekly reports from sales data.
Alexis Turner made an agent to extract key insights from research papers.
Sofia Martinez created an app to categorize support tickets automatically.
David Park Chung built an agent to convert PDFs into structured databases.
Rachel M Foster made an AI app to track project milestones from documents.
Amanda Zhang created an agent to analyze sentiment from customer reviews.
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