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A Road Map of Prompt Engineering for ChatGPT in Healthcare: A Perspective Study
Shahabeddin Abhari1, Somayeh Fatahi2, Ashish Saragadam1
1School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada.
Studies in Health Technology and Informatics
|August 23, 2024
Summary
Prompt engineering tailors Generative AI (Artificial Intelligence) for healthcare, creating a nine-stage process to meet diverse stakeholder needs and improve patient decision-making.
Area of Science:
- Artificial Intelligence in Medicine
- Health Informatics
- Biomedical Engineering
Background:
- Generative AI models like ChatGPT are transforming healthcare.
- Strategic prompt use is key to enhancing AI precision, relevance, and ethics.
- Healthcare stakeholders require tailored AI outputs for specific needs.
Purpose of the Study:
- To explore prompt engineering applications for healthcare stakeholders.
- To propose a systematic process for developing healthcare-specific AI prompts.
- To ensure AI-generated information supports informed decision-making.
Main Methods:
- Literature review on Generative AI, ChatGPT, prompts, and healthcare.
- Qualitative analysis and expert input to identify key prompts.
- Development of a nine-stage prompt engineering process for healthcare.
Main Results:
- A structured nine-stage process for healthcare prompt engineering is proposed.
- The process emphasizes stakeholder needs, ethical considerations, and iterative refinement.
- Identified key prompts tailored for patients, providers, policymakers, and researchers.
Conclusions:
- Systematic prompt engineering is crucial for effective Generative AI in healthcare.
- Tailored prompts enhance the utility of AI for diverse healthcare stakeholders.
- This approach supports improved patient understanding of symptoms, treatments, and prevention.
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