A scoping review of interpretability and explainability concerning artificial intelligence methods in medical imaging.

Champendal, Mélanie; Müller, Henning; Prior, John O; Dos Reis, Cláudia Sá

Champendal, Mélanie; Müller, Henning; Prior, John O; Dos Reis, Cláudia Sá.

Afiliación

Champendal M; School of Health Sciences HESAV, HES-SO, University of Applied Sciences Western Switzerland, Lausanne, CH, Switzerland; Faculty of Biology and Medicine, University of Lausanne, Lausanne, CH, Switzerland. Electronic address: melanie.champendal@hesav.ch.
Müller H; Informatics Institute, University of Applied Sciences Western Switzerland (HES-SO Valais) Sierre, CH, Switzerland; Medical faculty, University of Geneva, CH, Switzerland. Electronic address: henning.mueller@hevs.ch.
Prior JO; Faculty of Biology and Medicine, University of Lausanne, Lausanne, CH, Switzerland; Nuclear Medicine and Molecular Imaging Department, Lausanne University Hospital (CHUV), Lausanne, CH, Switzerland. Electronic address: john.prior@chuv.ch.
Dos Reis CS; School of Health Sciences HESAV, HES-SO, University of Applied Sciences Western Switzerland, Lausanne, CH, Switzerland. Electronic address: claudia.sadosreis@hesav.ch.

Eur J Radiol ; 169: 111159, 2023 Dec.

Article en En | MEDLINE | ID: mdl-37976760

Asunto(s)

Enfermedad de Alzheimer; Neoplasias Encefálicas; Humanos; Inteligencia Artificial; Radiografía; Encéfalo/diagnóstico por imagen

Palabras clave

Computed Tomography; Deep Learning; Explainability; Machine Learning; Magnetic Resonance Imaging (MRI); Medical Imaging; Radiography; Transparency

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Enfermedad de Alzheimer Tipo de estudio: Systematic_reviews Límite: Humans Idioma: En Revista: Eur J Radiol Año: 2023 Tipo del documento: Article Pais de publicación: Irlanda

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