Artificial intelligence in emergency and trauma radiology: ASER AI/ML expert panel Delphi consensus statement on research guidelines, practices, and priorities.

Autor: Dreizin D; Emergency and Trauma Imaging, Department of Diagnostic Radiology and Nuclear Medicine, R Adams Cowley Shock Trauma Center, University of Maryland School of Medicine, Baltimore, MD, USA. daviddreizin@gmail.com., Khatri G; Abdominal Imaging, Department of Radiology, University of Colorado, Denver, CO, USA., Staziaki PV; Cardiothoracic imaging, Department of Radiology, University of Vermont, Larner College of Medicine, Burlington, USA., Buch K; Neuroradiology imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA., Underbath M; Johns Hopkins University, Baltimore, MD, USA., Mohammed M; Abdominal imaging, Department of Radiology, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia., Sodickson A; Mass General Brigham Enterprise Emergency Radiology, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA., Khurana B; Trauma Imaging Research and innovation Center, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA., Agrawal A; Department of Radiology, Teleradiology Solutions, Delhi, India., Spann JS; Department of Radiology, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA., Beckmann N; McGovern Medical School at UTHealth, Houston, USA., DelProposto Z; Division of Emergency Radiology, Department of Radiology, University of Michigan, Ann Arbor, MI, USA., LeBedis CA; Department of Radiology, Boston Medical Center, Boston, MA, USA., Davis M; Department of Radiology, Yale University, New Haven, CT, USA., Dickerson G; University of Maryland School of Medicine, Baltimore, MD, USA., Lev M; Emergency Radiology, Department of Radiology, Massachusetts General Hospial, Boston, USA.

Publikováno v: Emergency radiology [Emerg Radiol] 2024 Dec 23. Date of Electronic Publication: 2024 Dec 23.