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.
Subject(s)
Internship and Residency , Radiology , Artificial Intelligence , Humans , Radiography , Radiologists , Radiology/educationABSTRACT
La inteligencia artificial (IA) es una rama de las ciencias computacionales que está generando enormes expectativas en la medicina en general y en la radiología en particular. La IA no va a alterar solo la forma en que ejercemos la radiología, sino que también va a impactar en el modo en que la enseñamos y la aprendemos. Aunque se ha llegado a cuestionar la necesidad de seguir formando radiólogos como consecuencia de la llegada de la IA, la literatura científica reciente parece estar de acuerdo en que debemos seguir formándolos, incorporando a su capacitación nuevos conocimientos y competencias en IA. Esta nueva formación debería comenzar en la fase universitaria, consolidarse durante la residencia y mantenerse durante la etapa de formación continuada. Este artículo pretende describir algunos de los desafíos que la IA puede plantear en las diferentes fases formativas del radiólogo, desde la educación universitaria hasta la formación continuada.(AU)
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.(AU)
Subject(s)
Humans , Male , Female , Artificial Intelligence , Radiography , Radiology/education , Professional Training , Education, Continuing , Radiology , Radiologists/educationABSTRACT
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.
