000127097 001__ 127097
000127097 005__ 20240731103351.0
000127097 0247_ $$2doi$$a10.1371/journal.pone.0289495
000127097 0248_ $$2sideral$$a134497
000127097 037__ $$aART-2023-134497
000127097 041__ $$aeng
000127097 100__ $$0(orcid)0000-0003-1270-5852$$aHernandez, Monica$$uUniversidad de Zaragoza
000127097 245__ $$aExplainable artificial intelligence toward usable and trustworthy computer-aided diagnosis of multiple sclerosis from Optical Coherence Tomography
000127097 260__ $$c2023
000127097 5060_ $$aAccess copy available to the general public$$fUnrestricted
000127097 5203_ $$aBackground: Several studies indicate that the anterior visual pathway provides information about the dynamics of axonal degeneration in Multiple Sclerosis (MS). Current research in the field is focused on the quest for the most discriminative features among patients and controls and the development of machine learning models that yield computer-aided solutions widely usable in clinical practice. However, most studies are conducted with small samples and the models are used as black boxes. Clinicians should not trust machine learning decisions unless they come with comprehensive and easily understandable explanations. Materials and methods: A total of 216 eyes from 111 healthy controls and 100 eyes from 59 patients with relapsing-remitting MS were enrolled. The feature set was obtained from the thickness of the ganglion cell layer (GCL) and the retinal nerve fiber layer (RNFL). Measurements were acquired by the novel Posterior Pole protocol from Spectralis Optical Coherence Tomography (OCT) device. We compared two black-box methods (gradient boosting and random forests) with a glass-box method (explainable boosting machine). Explainability was studied using SHAP for the black-box methods and the scores of the glass-box method. Results: The best-performing models were obtained for the GCL layer. Explainability pointed out to the temporal location of the GCL layer that is usually broken or thinning in MS and the relationship between low thickness values and high probability of MS, which is coherent with clinical knowledge.Conclusions: The insights on how to use explainability shown in this work represent a first important step toward a trustworthy computer-aided solution for the diagnosis of MS with OCT.
000127097 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T64-20R$$9info:eu-repo/grantAgreement/ES/ISCIII/PI17-01726$$9info:eu-repo/grantAgreement/ES/ISCIII/PI20-00437$$9info:eu-repo/grantAgreement/ES/ISCIII-RICORDS/RD21-0002-0050$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-104358RB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2022-138703OB-I00
000127097 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000127097 590__ $$a2.9$$b2023
000127097 592__ $$a0.839$$b2023
000127097 591__ $$aMULTIDISCIPLINARY SCIENCES$$b31 / 134 = 0.231$$c2023$$dQ1$$eT1
000127097 593__ $$aMultidisciplinary$$c2023$$dQ1
000127097 594__ $$a6.2$$b2023
000127097 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000127097 700__ $$aRamon-Julvez, Ubaldo$$uUniversidad de Zaragoza
000127097 700__ $$0(orcid)0000-0001-9411-5834$$aVilades, Elisa$$uUniversidad de Zaragoza
000127097 700__ $$aCordon, Beatriz$$uUniversidad de Zaragoza
000127097 700__ $$0(orcid)0000-0002-9109-5337$$aMayordomo, Elvira$$uUniversidad de Zaragoza
000127097 700__ $$0(orcid)0000-0001-6258-2489$$aGarcia-Martin, Elena$$uUniversidad de Zaragoza
000127097 7102_ $$11013$$2646$$aUniversidad de Zaragoza$$bDpto. Cirugía$$cÁrea Oftalmología
000127097 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000127097 773__ $$g18, 8 (2023), e0289495 [32 pp]$$pPLoS One$$tPLoS ONE$$x1932-6203
000127097 8564_ $$s5446815$$uhttps://zaguan.unizar.es/record/127097/files/texto_completo.pdf$$yVersión publicada
000127097 8564_ $$s2094824$$uhttps://zaguan.unizar.es/record/127097/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000127097 909CO $$ooai:zaguan.unizar.es:127097$$particulos$$pdriver
000127097 951__ $$a2024-07-31-09:54:29
000127097 980__ $$aARTICLE