{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:28:47Z","timestamp":1792790927836,"version":"4.5.0"},"reference-count":37,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T00:00:00Z","timestamp":1731283200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100020884","name":"Agencia Nacional de Investigaci\u00f3n y Desarrollo","doi-asserted-by":"publisher","award":["PIA\/PUENTE AFB230002"],"award-info":[{"award-number":["PIA\/PUENTE AFB230002"]}],"id":[{"id":"10.13039\/501100020884","id-type":"DOI","asserted-by":"publisher"}]},{"name":"FONDECYT-Chile","award":["12200007"],"award-info":[{"award-number":["12200007"]}]},{"name":"FONDECYT-Chile","award":["11191215"],"award-info":[{"award-number":["11191215"]}]},{"name":"FONDECYT-Chile","award":["1212038"],"award-info":[{"award-number":["1212038"]}]},{"name":"FONDECYT-Chile","award":["1200221"],"award-info":[{"award-number":["1200221"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Explainable Artificial Intelligence (XAI) is an emerging machine learning field that has been successful in medical image analysis. Interpretable approaches are able to \u201cunbox\u201d the black-box decisions made by AI systems, aiding medical doctors to justify their diagnostics better. In this paper, we analyze the performance of three different XAI strategies for medical image analysis in ophthalmology. We consider a multimodal deep learning model that combines optical coherence tomography (OCT) and infrared reflectance (IR) imaging for the diagnosis of age-related macular degeneration (AMD). The classification model is able to achieve an accuracy of 0.94, performing better than other unimodal alternatives. We analyze the XAI methods in terms of their ability to identify retinal damage and ease of interpretation, concluding that grad-CAM and guided grad-CAM can be combined to have both a coarse visual justification and a fine-grained analysis of the retinal layers. We provide important insights and recommendations for practitioners on how to design automated and explainable screening tests based on the combination of two image sources.<\/jats:p>","DOI":"10.1371\/journal.pone.0311811","type":"journal-article","created":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T18:26:53Z","timestamp":1731349613000},"page":"e0311811","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":11,"title":["Interpretable multimodal classification for age-related macular degeneration diagnosis"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4612-1409","authenticated-orcid":true,"given":"Carla","family":"Vairetti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebasti\u00e1n","family":"Maldonado","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Loreto","family":"Cuitino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cristhian A.","family":"Urzua","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,11,11]]},"reference":[{"key":"pone.0311811.ref001","article-title":"Clinical performance of predicting late age-related macular degeneration development using multimodal imaging","author":"KL Goh","year":"2024","journal-title":"Clinical & Experimental Ophthalmology"},{"issue":"7","key":"pone.0311811.ref002","first-page":"2273","article-title":"Multimodal Assessment of OCT-derived Biomarkers of Geographic Atrophy (GA) and its Precursors","volume":"65","author":"J Winkler","year":"2024","journal-title":"Investigative Ophthalmology & Visual Science"},{"issue":"12","key":"pone.0311811.ref003","doi-asserted-by":"crossref","first-page":"1674","DOI":"10.1016\/j.ophtha.2020.05.036","article-title":"Deep learning automated detection of reticular pseudodrusen from fundus autofluorescence images or color fundus photographs in AREDS2","volume":"127","author":"TD Keenan","year":"2020","journal-title":"Ophthalmology"},{"issue":"1","key":"pone.0311811.ref004","doi-asserted-by":"crossref","first-page":"8396","DOI":"10.1038\/s41598-023-35394-z","article-title":"Multimodal imaging of laser-induced choroidal neovascularization in pigmented rabbits","volume":"13","author":"VP Nguyen","year":"2023","journal-title":"Scientific Reports"},{"issue":"1","key":"pone.0311811.ref005","doi-asserted-by":"crossref","first-page":"e126","DOI":"10.1111\/aos.15708","article-title":"Assessment of intraretinal hyperreflective foci using multimodal imaging in eyes with age-related macular degeneration","volume":"102","author":"D Oncel","year":"2024","journal-title":"Acta ophthalmologica"},{"issue":"3","key":"pone.0311811.ref006","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.oret.2022.08.018","article-title":"Deep learning to predict geographic atrophy area and growth rate from multimodal imaging","volume":"7","author":"N Anegondi","year":"2023","journal-title":"Ophthalmology Retina"},{"issue":"195","key":"pone.0311811.ref007","first-page":"e65240","article-title":"Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration","author":"JD Messinger","year":"2023","journal-title":"JoVE (Journal of Visualized Experiments)"},{"issue":"1","key":"pone.0311811.ref008","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1097\/IIO.0000000000000512","article-title":"Imaging Modalities for Dry Macular Degeneration","volume":"64","author":"A Samanta","year":"2024","journal-title":"International Ophthalmology Clinics"},{"issue":"4","key":"pone.0311811.ref009","doi-asserted-by":"crossref","first-page":"100311","DOI":"10.1016\/j.xops.2023.100311","article-title":"Deep-GA-Net for Accurate and Explainable Detection of Geographic Atrophy on OCT Scans","volume":"3","author":"A Elsawy","year":"2023","journal-title":"Ophthalmology Science"},{"key":"pone.0311811.ref010","doi-asserted-by":"crossref","first-page":"101111","DOI":"10.1016\/j.preteyeres.2022.101111","article-title":"Quantitative approaches in multimodal fundus imaging: state of the art and future perspectives","volume":"92","author":"A Arrigo","year":"2023","journal-title":"Progress in Retinal and Eye Research"},{"key":"pone.0311811.ref011","unstructured":"Tasnim N, Hasan M, Islam I. 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