@article{LUO2024, 
author = {Xufei LUO and Han LYU and Zaiwei SONG and Hui LIU and Zhixiang WANG and Haodong LI and Ye WANG and Di ZHU and Lu ZHANG and Yaolong CHEN},
title = {The Impact of Generative Artificial Intelligence on the Development, Evaluation, and Application of Clinical Practice Guidelines},
year = {2024},
journal = {Medical Journal of Peking Union Medical College Hospital},
volume = {15},
number = {5},
pages = {1173-1181},
keywords = {clinical practice guideline, generative artificial intelligence, systematic review, ChatGPT, large language models},
url = {https://www.sciopen.com/article/10.12290/xhyxzz.2024-0602},
doi = {10.12290/xhyxzz.2024-0602},
abstract = {Generative artificial intelligence (GAI) refers to AI technology capable of generating new content such as text, images, or audio from training data. GAI tools not only demonstrate rapid and efficient potential in literature screening, data extraction, and literature appraisal in systematic reviews, but can also be used for guideline evaluation and dissemination, enhancing the readability and promotion efficiency of guidelines. However, the accuracy of content generated by GAI tools, the rationality of cited evidence, the level of evidence, and the reliability of data still need verification. Additionally, data privacy protection and ethical issues are challenges that need to be addressed. This article aims to overview the current status of GAI tools in the formulation, evaluation, dissemination, and implementation of guidelines, explore the feasibility and new models of GAI tools in the field of guidelines, and improve the efficiency and quality of guideline formulation to better serve guideline developers and users.}
}