Expert consensus on the construction and quality control of datasets for artificial intelligence(AI)assisted blastocyst morphometric assessment
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.
Artificial intelligence(AI)Blastocyst morphology assessmentData set constructionData set annotationData set quality control
国家科技期刊平台
NSTL
万方数据
