David Dreizin, Garvit Khatri, Pedro V Staziaki, Karen Buch, Mathias Unberath, Mohammed Mohammed, Aaron Sodickson, Bharti Khurana, Anjali Agrawal, James Stephen Spann, Nicholas Beckmann, Zachary DelProposto, Christina A LeBedis, Melissa Davis, Gabrielle Dickerson, Michael Lev
{"title":"更正:急诊和创伤放射学中的人工智能:ASER AI/ML专家小组关于研究指南、实践和优先事项的德尔菲共识声明。","authors":"David Dreizin, Garvit Khatri, Pedro V Staziaki, Karen Buch, Mathias Unberath, Mohammed Mohammed, Aaron Sodickson, Bharti Khurana, Anjali Agrawal, James Stephen Spann, Nicholas Beckmann, Zachary DelProposto, Christina A LeBedis, Melissa Davis, Gabrielle Dickerson, Michael Lev","doi":"10.1007/s10140-025-02312-x","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Correction to: Artificial intelligence in emergency and trauma radiology: ASER AI/ML expert panel Delphi consensus statement on research guidelines, practices, and priorities.\",\"authors\":\"David Dreizin, Garvit Khatri, Pedro V Staziaki, Karen Buch, Mathias Unberath, Mohammed Mohammed, Aaron Sodickson, Bharti Khurana, Anjali Agrawal, James Stephen Spann, Nicholas Beckmann, Zachary DelProposto, Christina A LeBedis, Melissa Davis, Gabrielle Dickerson, Michael Lev\",\"doi\":\"10.1007/s10140-025-02312-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":11623,\"journal\":{\"name\":\"Emergency Radiology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2025-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Emergency Radiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s10140-025-02312-x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Emergency Radiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10140-025-02312-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Correction to: Artificial intelligence in emergency and trauma radiology: ASER AI/ML expert panel Delphi consensus statement on research guidelines, practices, and priorities.
期刊介绍:
To advance and improve the radiologic aspects of emergency careTo establish Emergency Radiology as an area of special interest in the field of diagnostic imagingTo improve methods of education in Emergency RadiologyTo provide, through formal meetings, a mechanism for presentation of scientific papers on various aspects of Emergency Radiology and continuing educationTo promote research in Emergency Radiology by clinical and basic science investigators, including residents and other traineesTo act as the resource body on Emergency Radiology for those interested in emergency patient care Members of the American Society of Emergency Radiology (ASER) receive the Emergency Radiology journal as a benefit of membership!