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Challenges of Radiology education in the era of artificial intelligence.
Gorospe-Sarasúa, L; Muñoz-Olmedo, J M; Sendra-Portero, F; de Luis-García, R.
Affiliation
  • Gorospe-Sarasúa L; Servicio de Radiodiagnóstico, Hospital Universitario Ramón y Cajal, Madrid, Spain. Electronic address: luisgorospe@yahoo.com.
  • Muñoz-Olmedo JM; Servicio de Radiodiagnóstico, Hospital Universitario de La Princesa, Madrid, Spain.
  • Sendra-Portero F; Servicio de Radiología y Medicina Física, Facultad de Medicina, Universidad de Málaga, Málaga, Spain.
  • de Luis-García R; Escuela de Ingeniería de Telecomunicaciones, Universidad de Valladolid, Valladolid, Spain.
Radiologia (Engl Ed) ; 64(1): 54-59, 2022.
Article in En | MEDLINE | ID: mdl-35180987
ABSTRACT
Artificial intelligence is a branch of computer science that is generating great expectations in medicine and particularly in radiology. Artificial intelligence will change not only the way we practice our profession, but also the way we teach it and learn it. Although the advent of artificial intelligence has led some to question whether it is necessary to continue training radiologists, there seems to be a consensus in the recent scientific literature that we should continue to train radiologists and that we should teach future radiologists about artificial intelligence and how to exploit it. The acquisition of competency in artificial intelligence should start in medical school, be consolidated in residency programs, and be maintained and updated during continuing medical education. This article aims to describe some of the challenges that artificial intelligencve can pose in the different stages of training in radiology, from medical school through continuing medical education.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiology / Internship and Residency Type of study: Diagnostic_studies Limits: Humans Language: En Journal: Radiologia (Engl Ed) Year: 2022 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiology / Internship and Residency Type of study: Diagnostic_studies Limits: Humans Language: En Journal: Radiologia (Engl Ed) Year: 2022 Document type: Article