生殖医学杂志2024，Vol.33Issue(7)：843-851,9.DOI:10.3969/j.issn.1004-3845.2024.07.001
人工智能囊胚形态评估数据集构建与质控专家共识
Expert consensus on the construction and quality control of datasets for artificial intelligence(AI)assisted blastocyst morphometric assessment
摘要
Abstract
Computer assisted assessment of blastocyst morphology is an emerging direction in the artificial intelligence(AI)medical devices and an important application of AI in the field of assisted reproduction.In the initial stage of the application of AI in new fields,the construction and quality control of data sets have an important impact on product quality.At present,AI-assisted blastocyst morphology assessment has not yet formed a unified specification in terms of data collection,labeling,and quality control.Based on the existing national industry standards for AI medical devices and assisted reproduction medical devices,this paper discusses the requirements for data set construction and quality control and analyzes the quality characteristics of data sets with the theme of blastocyst morphology assessment datasets,with the aim of guiding data set manufacturers to strengthen the management of datasets in the whole life cycle,and to better provide quality assurance for the product research and development,testing,and clinical trials in order to help the development of the industry.关键词
人工智能(AI)/囊胚形态评估/数据集构建/数据集标注/数据集质量控制Key words
Artificial intelligence(AI)/Blastocyst morphology assessment/Data set construction/Data set annotation/Data set quality control分类
医药卫生引用本文复制引用
王浩,郝桂敏,卢文红,沈浣,师娟子,张松英,滕晓明,王晓红,王秀霞,伍琼芳,全松,张孝东,曾勇,钟影,邵小光,柯林楠,毛歆,韩倩倩,黄国宁,孙莹璞,孙海翔,邓成艳,黄学锋,刘平,周灿权,冯云..人工智能囊胚形态评估数据集构建与质控专家共识[J].生殖医学杂志,2024,33(7):843-851,9.基金项目
重庆市技术创新与应用发展专项项目(CSTB2022TIAD-KPX0146) （CSTB2022TIAD-KPX0146）
国家自然科学基金面上项目(82371728) （82371728）
