一句话：提出梳理 LLM 辅助医疗应用供应链中的软件最佳实践，以促进安全、负责任的医疗应用交付。
大型语言模型在医疗应用中具有提升诊断准确性、改善医患沟通和提升医疗效率的潜力，能处理海量数据、生成简洁信息并自动化任务。近期研究与现实案例表明，交付安全且负责任的 LLM 辅助应用至关重要。本文是一篇展望性手稿，作者说明其目标是揭示 LLM 医疗应用供应链中的最佳软件实践。摘要未报告具体方法、案例或实验结果，仅阐述研究意图。
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.
DOI 原文 ·
@inproceedings{paperbot9595,
title = {Best practice for supply chain in LLM-assisted medical applications},
author = {Shengming Zhao and Jiawei Wang},
booktitle = {ISSTA},
year = {2025},
doi = {10.1145/3713081.3731748}
}