ISSTA2025

Best practice for supply chain in LLM-assisted medical applications

Shengming Zhao, Jiawei Wang

Abstract

The application of large language models in medical applications is crucial for enhancing diagnostic accuracy, improving patient communication, and boosting healthcare efficiency. Their ability to process vast amounts of data, generate concise information, and automate tasks positions LLM applications as transformative tools. Recent studies and real-world examples underscore the importance of delivering secure and responsible LLM-assisted applications. In this manuscript, we outline our intention of uncovering best software practices in the supply chain of LLM medical applications.