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Vol. 64. Issue 4.
Pages 324-332 (July - August 2022)
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Vol. 64. Issue 4.
Pages 324-332 (July - August 2022)
Update in Radiology
Barriers to artificial intelligence implementation in radiology practice: What the radiologist needs to know
Dificultades en la implantación de la inteligencia artificial en la práctica radiológica: lo que el radiólogo necesita saber
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A.V. Naira,
Corresponding author
dranirudhnair@gmail.com

Corresponding author.
, S. Ramanathanb, P. Sathiadossc, A. Jajodiad, D. Blair Macdonalde
a Departamento de Imagenología Clínica, Hospital Al-Wakra, Hamad Medical Corporation, Doha, Qatar
b Departamento de Radiología, Weill Cornell Medicine, Departamento de Imagenología Clínica, Hospital Al-Wakra, Hamad Medical Corporation, Doha, Qatar
c Departamento de Radiología, The Ottawa Hospital, Universidad de Ottawa, Ottawa, Ontario, Canada
d Departamento de Radiología, Juravinski Cancer Center y St. Josephs Healthcare, Universidad McMaster, Hamilton, Canada
e Departamento de Radiología, Universidad de Ottawa, Ottawa, Ontario, Canada
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Abstract

Artificial Intelligence has the potential to disrupt the way clinical radiology is practiced globally. However, there are barriers that radiologists should be aware of prior to implementing Artificial Intelligence in daily practice. Barriers include regulatory compliance, ethical issues, data privacy, cybersecurity, AI training bias, and safe integration of AI into routine practice. In this article, we summarize the issues and the impact on clinical radiology.

Keywords:
Artificial intelligence
Machine learning
Practice
Software
Abbreviations:
AI
CNN
ML
Resumen

La inteligencia artificial (IA) ofrece la posibilidad de alterar la práctica de la radiología clínica en todo el mundo. Sin embargo, existen barreras que los radiólogos deben conocer antes de aplicar la inteligencia artificial en la práctica diaria. Las barreras incluyen cuestiones de cumplimiento de la reglamentación, cuestiones éticas, aspectos relacionados con la privacidad de los datos y la ciberseguridad, el sesgo de aprendizaje automático y la integración segura de la IA en la práctica habitual. En este artículo, resumimos estas cuestiones y su repercusión en la radiología clínica.

Palabras clave:
Inteligencia artificial
Aprendizaje automático
Práctica
Programa informático

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