Assessment of automatic decision-support systems for detecting active T2 lesions in multiple sclerosis patients.

Àlex RoviraJuan Francisco CorralCristina AugerSergi ValverdeÁngela Vidal-JordanaArnau OliverAndrea de BarrosYiken Karelys Ng WongMar TintoreDeborah ParetoFrancesc Xavier AymerichXavier MontalbanXavier Lladó Juli Alonso

Published in: Multiple sclerosis (Houndmills, Basingstoke, England) (2021)

Automated convolutional neural network models show potential as an aid to neuroradiological assessment in clinical practice, although visual supervision of the outcomes is still required.

Keyphrases

deep learning
convolutional neural network
multiple sclerosis
end stage renal disease
clinical practice
ejection fraction
newly diagnosed
machine learning
chronic kidney disease
prognostic factors
peritoneal dialysis
adipose tissue
risk assessment
climate change
skeletal muscle
neural network
single cell