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Destination: mk:H2_4 Item: Title: 2.3 Proposed CNN method Destination: mk:H2_5 Children: Item: Title: 2.3.1 Network architecture Destination: mk:H3_6 Item: Title: 2.3.2 Training procedure Destination: mk:H3_7 Item: Title: 2.3.3 Inference Destination: mk:H3_8 Item: Title: 2.4 Logistic regression model Destination: mk:H2_9 Item: Title: 2.5 External validation Destination: mk:H2_10 Item: Title: 2.6 Attention Maps: LRP Destination: mk:H2_11 Children: Item: Title: 2.6.1 Individual attention map analyses Destination: mk:H3_12 Item: Title: 2.6.2 Class-average attention map analyses Destination: mk:H3_13 Item: Title: 2.6.3 Voxel-wise regression to explain individual attention maps Destination: mk:H3_14 Item: Title: 2.7 Evaluation measures of the classification models Destination: mk:H2_15 Item: Title: 2.8 Descriptive statistics and other general aspects Destination: mk:H2_16 Item: Title: 3 Results Destination: mk:H1_3 Children: Item: Title: 3.1 Evaluation of DL-models: in-house dataset Destination: mk:H2_17 Item: Title: 3.2 Comparison with a LR-model Destination: mk:H2_18 Item: Title: 3.3 External validation dataset Destination: mk:H2_19 Item: Title: 3.4 DL-based attention maps analyses Destination: mk:H2_20 Children: Item: Title: 3.4.1 Individual attention maps Destination: mk:H3_21 Item: Title: 3.4.2 Class-average attention maps Destination: mk:H3_22 Item: Title: 3.4.3 Voxel-wise regression analyses Destination: mk:H3_23 Item: Title: 4 Discussion Destination: mk:H1_4 Item: Title: 5 Conclusions Destination: mk:H1_5 Item: Title: CRediT authorship contribution statement Destination: mk:H1_6 Item: Title: Declaration of Competing Interest Destination: mk:HH1_2 Item: Title: Data availability Destination: datalink3 Item: Title: Acknowledgments Destination: mk:H1_7 Item: Title: Appendix A Supplementary data Destination: mk:H1_8 Item: Title: References Destination: mk:HH2_1 Info: Title: Deciphering multiple sclerosis disability with deep learning attention maps on clinical 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NeuroImage: Clinical, 38 (2023) 103376. doi:10.1016/j.nicl.2023.103376 Multiple sclerosis Structural MRI Deep learning Attention maps Disability Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI Llucia Coll Deborah Pareto Pere Carbonell-Mirabent Álvaro Cobo-Calvo Georgina Arrambide Ángela Vidal-Jordana Manuel Comabella Joaquín Castilló Breogán Rodríguez-Acevedo Ana Zabalza Ingrid Galán Luciana Midaglia Carlos Nos Annalaura Salerno Cristina Auger Manel Alberich Jordi Río Jaume Sastre-Garriga Arnau Oliver Xavier Montalban Àlex Rovira Mar Tintoré Xavier Lladó Carmen Tur journal NeuroImage: Clinical © 2023 The Authors. Published by Elsevier Inc. 2213-1582 38 18 March 2023 2023-01-01 103376 103376 10.1016/j.nicl.2023.103376 https://doi.org/10.1016/j.nicl.2023.103376 http://creativecommons.org/licenses/by-nc-nd/4.0/ VoR 10.1016/j.nicl.2023.103376 noindex 18th March 2023 Elsevier 2023-03-17T23:15:19 2023-03-17T16:05:42 2023-03-17T23:15:19 True 18th March 2023 Acrobat Distiller 8.1.0 (Windows) Multiple sclerosis,Structural MRI,Deep learning,Attention maps,Disability uuid:1b499bed-4ce8-4c0c-b682-0d58baae1cbe uuid:b6ed5266-03cb-4855-90c0-636283357f42 Pages: Page: Label: 1 Annotations: Annotation: Subtype: Link Rect: 89, 571, 175, 582 Flags: Print Destination: 814 Annotation: Subtype: Link Rect: 175, 571, 303, 582 Flags: Print Destination: 814 Annotation: Subtype: Link Rect: 303, 571, 410, 582 Flags: Print Destination: 814 Annotation: Subtype: Link Rect: 135, 558, 444, 569 Flags: Print Destination: 814 Annotation: Subtype: Link Rect: 171, 545, 476, 556 Flags: Print Destination: 814 Annotation: Subtype: Link 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