Ryan C. L. Brewster, Matthew Nagy, Susmitha Wunnava, Florence T. Bourgeois
{"title":"美国 FDA 批准儿科人工智能和机器学习医疗设备","authors":"Ryan C. L. Brewster, Matthew Nagy, Susmitha Wunnava, Florence T. Bourgeois","doi":"10.1001/jamapediatrics.2024.5437","DOIUrl":null,"url":null,"abstract":"This cross-sectional study analyzes the availability of artificial intelligence and machine learning–enabled devices authorized for children by the US Food and Drug Administration (FDA) and assesses reporting of algorithm validation in the pediatric population.","PeriodicalId":14683,"journal":{"name":"JAMA Pediatrics","volume":"252 1","pages":""},"PeriodicalIF":24.7000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"US FDA Approval of Pediatric Artificial Intelligence and Machine Learning–Enabled Medical Devices\",\"authors\":\"Ryan C. L. Brewster, Matthew Nagy, Susmitha Wunnava, Florence T. Bourgeois\",\"doi\":\"10.1001/jamapediatrics.2024.5437\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This cross-sectional study analyzes the availability of artificial intelligence and machine learning–enabled devices authorized for children by the US Food and Drug Administration (FDA) and assesses reporting of algorithm validation in the pediatric population.\",\"PeriodicalId\":14683,\"journal\":{\"name\":\"JAMA Pediatrics\",\"volume\":\"252 1\",\"pages\":\"\"},\"PeriodicalIF\":24.7000,\"publicationDate\":\"2024-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JAMA Pediatrics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1001/jamapediatrics.2024.5437\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PEDIATRICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JAMA Pediatrics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1001/jamapediatrics.2024.5437","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PEDIATRICS","Score":null,"Total":0}
US FDA Approval of Pediatric Artificial Intelligence and Machine Learning–Enabled Medical Devices
This cross-sectional study analyzes the availability of artificial intelligence and machine learning–enabled devices authorized for children by the US Food and Drug Administration (FDA) and assesses reporting of algorithm validation in the pediatric population.
期刊介绍:
JAMA Pediatrics, the oldest continuously published pediatric journal in the US since 1911, is an international peer-reviewed publication and a part of the JAMA Network. Published weekly online and in 12 issues annually, it garners over 8.4 million article views and downloads yearly. All research articles become freely accessible online after 12 months without any author fees, and through the WHO's HINARI program, the online version is accessible to institutions in developing countries.
With a focus on advancing the health of infants, children, and adolescents, JAMA Pediatrics serves as a platform for discussing crucial issues and policies in child and adolescent health care. Leveraging the latest technology, it ensures timely access to information for its readers worldwide.