摘要
随着互联网技术的发展,涌现了大量网络健康资料,但这些资料质量参差不齐,可靠性和可读性有待提高。如何评估网络健康资料质量,成为困扰医护人员和患者的现实问题。机器学习在海量数据分析中的优势作用,为高效评估网络健康资料质量提供了可能。本文将从机器学习在网络健康资料可靠性、可读性等方面的研究进展进行综述,为编写精准可读的健康教育资料提供参考。
With the development of internet technology,a large number of online health data have emerged,but the quality of these data is uneven,and their reliability and readability need to be improved.How to evaluate the quality of online health data has become a practical problem that troubles medical staff and patients.The advantageous role of machine learning in massive data analysis provides the possibility for efficient evaluation of the quality of online health information.This paper reviewed the research progress of machine learning in the reliability and readability of online health data,and providedreference for writing accurate and readable health education materials.
作者
邹静
丁福
ZOU Jing;DING Fu(Department of Burns and Medical Cosmetology,the First Affiliated Hospital,Chongqing Medical University,Chongqing 400016,China;Department ofNursing,the First Affiliated Hospital,Chongqing Medical University,Chongqing 400016,China)
出处
《护士进修杂志》
2024年第12期1291-1295,共5页
Journal of Nurses Training
基金
重庆市技术创新与应用发展专项重点项目(编号:CSTB2022TIAD-KPX0165)
重庆医科大学智慧医学研究项目(编号:ZHYX202226)。
关键词
机器学习
网络健康资料
质量
可靠性
可读性
综述
machine learning
online health data
quality
reliability
readability
review
