Large Language Models in Healthcare: Prompt Engineering Competition

This tutorial/competition explores prompt engineering for large language models (LLMs) with a focus on OpenAI's ChatGPT, such as GPT-4o or GPT-4o-mini, showcasing the potential usefulness in healthcare. It is structured in two parts: 1) a practical tutorial focusing on advanced prompt engineering methods and highlighting privacy requirements, such as HIPAA, GDPR, in healthcare and 2) a hands-on part in the form of a prompt engineering competition. Participants will be asked to find the best solution for a specific healthcare related task on healthcare data using free OpenAI ChatGPT. The intended audience are healthcare researchers and professionals, AI scientists, data scientists, and PhD students in the relevant fields as well as others. Attendees will gain insights into prompt engineering strategies and get insights how desirable outcomes for specific tasks can be achieved. This tutorial aims to educate participants with the knowledge on how to improve utilization of LLMs in healthcare and encourage creative thinking in solving real-world problems in healthcare.

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Publication Details

Published
2025-06-18
DOI
https://doi.org/10.1109/ichi64645.2025.00105
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Large Language Models in Healthcare: Prompt Engineering Competition

Lucija Gosak, Gregor Štiglic, Primož Kocbek
Artificial Intelligence in Healthcare and Education
article

Large Language Models in Healthcare: Prompt Engineering Competition

Lucija Gosak, Gregor Štiglic, Primož Kocbek
article en

Abstract

This tutorial/competition explores prompt engineering for large language models (LLMs) with a focus on OpenAI's ChatGPT, such as GPT-4o or GPT-4o-mini, showcasing the potential usefulness in healthcare. It is structured in two parts: 1) a practical tutorial focusing on advanced prompt engineering methods and highlighting privacy requirements, such as HIPAA, GDPR, in healthcare and 2) a hands-on part in the form of a prompt engineering competition. Participants will be asked to find the best solution for a specific healthcare related task on healthcare data using free OpenAI ChatGPT. The intended audience are healthcare researchers and professionals, AI scientists, data scientists, and PhD students in the relevant fields as well as others. Attendees will gain insights into prompt engineering strategies and get insights how desirable outcomes for specific tasks can be achieved. This tutorial aims to educate participants with the knowledge on how to improve utilization of LLMs in healthcare and encourage creative thinking in solving real-world problems in healthcare.

University of Maribor (SI)
Industry, innovation and infrastructure
Openalex Percentile: Top 88%
Artificial Intelligence in Healthcare and Education
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