{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T04:25:08Z","timestamp":1778127908648,"version":"3.51.4"},"reference-count":50,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2019,12,3]],"date-time":"2019-12-03T00:00:00Z","timestamp":1575331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Secretariat of State for Research, Development and Innovation","award":["DPI2017-88438-R"],"award-info":[{"award-number":["DPI2017-88438-R"]}]},{"DOI":"10.13039\/501100004587","name":"Instituto de Salud Carlos III","doi-asserted-by":"publisher","award":["PI17\/01726"],"award-info":[{"award-number":["PI17\/01726"]}],"id":[{"id":"10.13039\/501100004587","id-type":"DOI","asserted-by":"publisher"}]},{"name":"RETICS Oftared","award":["RD16\/0008\/020"],"award-info":[{"award-number":["RD16\/0008\/020"]}]},{"name":"RETICS Oftared","award":["RD16\/0008\/029"],"award-info":[{"award-number":["RD16\/0008\/029"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The purpose of this paper is to evaluate the feasibility of diagnosing multiple sclerosis (MS) using optical coherence tomography (OCT) data and a support vector machine (SVM) as an automatic classifier. Forty-eight MS patients without symptoms of optic neuritis and forty-eight healthy control subjects were selected. Swept-source optical coherence tomography (SS-OCT) was performed using a DRI (deep-range imaging) Triton OCT device (Topcon Corp., Tokyo, Japan). Mean values (right and left eye) for macular thickness (retinal and choroidal layers) and peripapillary area (retinal nerve fibre layer, retinal, ganglion cell layer\u2014GCL, and choroidal layers) were compared between both groups. Based on the analysis of the area under the receiver operator characteristic curve (AUC), the 3 variables with the greatest discriminant capacity were selected to form the feature vector. A SVM was used as an automatic classifier, obtaining the confusion matrix using leave-one-out cross-validation. Classification performance was assessed with Matthew\u2019s correlation coefficient (MCC) and the AUCCLASSIFIER. The most discriminant variables were found to be the total GCL++ thickness (between inner limiting membrane to inner nuclear layer boundaries), evaluated in the peripapillary area and macular retina thickness in the nasal quadrant of the outer and inner rings. Using the SVM classifier, we obtained the following values: MCC = 0.81, sensitivity = 0.89, specificity = 0.92, accuracy = 0.91, and AUCCLASSIFIER = 0.97. Our findings suggest that it is possible to classify control subjects and MS patients without previous optic neuritis by applying machine-learning techniques to study the structural neurodegeneration in the retina.<\/jats:p>","DOI":"10.3390\/s19235323","type":"journal-article","created":{"date-parts":[[2019,12,4]],"date-time":"2019-12-04T04:30:35Z","timestamp":1575433835000},"page":"5323","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":71,"title":["Computer-Aided Diagnosis of Multiple Sclerosis Using a Support Vector Machine and Optical Coherence Tomography Features"],"prefix":"10.3390","volume":"19","author":[{"given":"Carlo","family":"Cavaliere","sequence":"first","affiliation":[{"name":"Biomedical Engineering Group, Department of Electronics, University of Alcal\u00e1, 28801 Alcal\u00e1 de Henares, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9411-5834","authenticated-orcid":false,"given":"Elisa","family":"Vilades","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Miguel Servet University Hospital, 50009 Zaragoza, Spain"},{"name":"Aragon Institute for Health Research (IIS Aragon), Miguel Servet Ophthalmology Innovation and Research Group (GIMSO), University of Zaragoza, 50009 Zaragoza, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M\u00aa","family":"Alonso-Rodr\u00edguez","sequence":"additional","affiliation":[{"name":"Department of Physics and Mathematics, University of Alcal\u00e1, 28801 Alcal\u00e1 de Henares, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4009-3075","authenticated-orcid":false,"given":"Mar\u00eda","family":"Rodrigo","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Miguel Servet University Hospital, 50009 Zaragoza, Spain"},{"name":"Aragon Institute for Health Research (IIS Aragon), Miguel Servet Ophthalmology Innovation and Research Group (GIMSO), University of Zaragoza, 50009 Zaragoza, Spain"},{"name":"RETICS-Oftared: Thematic Networks for Co-operative Research in Health for Ocular Diseases, 28040 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luis","family":"Pablo","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Miguel Servet University Hospital, 50009 Zaragoza, Spain"},{"name":"Aragon Institute for Health Research (IIS Aragon), Miguel Servet Ophthalmology Innovation and Research Group (GIMSO), University of Zaragoza, 50009 Zaragoza, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4641-5848","authenticated-orcid":false,"given":"Juan","family":"Miguel","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Group, Department of Electronics, University of Alcal\u00e1, 28801 Alcal\u00e1 de Henares, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elena","family":"L\u00f3pez-Guill\u00e9n","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Group, Department of Electronics, University of Alcal\u00e1, 28801 Alcal\u00e1 de Henares, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eva","family":"Morla","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, 12 Octubre University Hospital Research Institute (i+12), 28041 Madrid, Spain"},{"name":"Faculty of Medicine, Complutense University of Madrid, 28040 Madrid, Spain"},{"name":"CIBERSAM: Biomedical Research Networking Centre in Mental Health, 28029 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8591-6103","authenticated-orcid":false,"given":"Luciano","family":"Boquete","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Group, Department of Electronics, University of Alcal\u00e1, 28801 Alcal\u00e1 de Henares, Spain"},{"name":"RETICS-Oftared: Thematic Networks for Co-operative Research in Health for Ocular Diseases, 28040 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elena","family":"Garcia-Martin","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Miguel Servet University Hospital, 50009 Zaragoza, Spain"},{"name":"Aragon Institute for Health Research (IIS Aragon), Miguel Servet Ophthalmology Innovation and Research Group (GIMSO), University of Zaragoza, 50009 Zaragoza, Spain"},{"name":"RETICS-Oftared: Thematic Networks for Co-operative Research in Health for Ocular Diseases, 28040 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"101459","DOI":"10.1016\/j.msard.2019.101459","article-title":"Consensus recommendations for the diagnosis and treatment of multiple sclerosis: 2019 revisions to the MENACTRIMS guidelines","volume":"37","author":"Yamout","year":"2020","journal-title":"Mult. Scler. Relat. Disord."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1177\/1756285617708911","article-title":"MRI in the assessment and monitoring of multiple sclerosis: An update on best practice","volume":"10","author":"Kaunzner","year":"2017","journal-title":"Ther. Adv. Neurol. Disord."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1097\/WNO.0b013e318238937f","article-title":"Vision in multiple sclerosis: The story, structure-function correlations, and models for neuroprotection","volume":"31","author":"Sakai","year":"2011","journal-title":"J. Neuroophthalmol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.1126\/science.1957169","article-title":"Optical coherence tomography","volume":"254","author":"Huang","year":"1991","journal-title":"Science"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"P\u00e9rez Del Palomar, A., Cego\u00f1ino, J., Montol\u00edo, A., Orduna, E., Vilades, E., Sebasti\u00e1n, B., Pablo, L.E., and Garcia-Martin, E. (2019). Swept source optical coherence tomography to early detect multiple sclerosis disease. The use of machine learning techniques. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0216410"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3248","DOI":"10.1364\/BOE.8.003248","article-title":"Twenty-five years of optical coherence tomography: The paradigm shift in sensitivity and speed provided by Fourier domain OCT [Invited]","volume":"8","author":"Leitgeb","year":"2017","journal-title":"Biomed. Opt. Express"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"20029","DOI":"10.1364\/OE.18.020029","article-title":"Ultrahigh speed 1050nm swept source\/Fourier domain OCT retinal and anterior segment imaging at 100,000 to 400,000 axial scans per second","volume":"18","author":"Potsaid","year":"2010","journal-title":"Opt. Express"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s40135-018-0158-3","article-title":"Swept Source Optical Coherence Tomography: A Review","volume":"6","author":"Or","year":"2018","journal-title":"Curr. Ophthalmol. Rep."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4971","DOI":"10.1167\/iovs.11-7729","article-title":"Macular choroidal thickness and volume in normal subjects measured by swept-source optical coherence tomography. Invest","volume":"52","author":"Hirata","year":"2011","journal-title":"Ophthalmol. Vis. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1136\/bjophthalmol-2013-303904","article-title":"Direct comparison of spectral-domain and swept-source OCT in the measurement of choroidal thickness in normal eyes","volume":"98","author":"Copete","year":"2014","journal-title":"Br. J. Ophthalmol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"13365","DOI":"10.1364\/OE.24.013365","article-title":"MEMS-based handheld scanning probe with pre-shaped input signals for distortion-free images in Gabor-domain optical coherence microscopy","volume":"24","author":"Cogliati","year":"2016","journal-title":"Opt. Express"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4124","DOI":"10.1167\/iovs.10-6643","article-title":"Fourier-domain OCT in multiple sclerosis patients: Reproducibility and ability to detect retinal nerve fiber layer atrophy","volume":"52","author":"Pueyo","year":"2011","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1097\/WCO.0000000000000604","article-title":"Optical coherence tomography as a means to characterize visual pathway involvement in multiple sclerosis","volume":"31","author":"Wicki","year":"2018","journal-title":"Curr. Opin. Neurol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1016\/S1474-4422(16)00068-5","article-title":"Retinal thickness measured with optical coherence tomography and risk of disability worsening in multiple sclerosis: A cohort study","volume":"15","author":"Arnow","year":"2016","journal-title":"Lancet Neurol."},{"key":"ref_15","first-page":"2520","article-title":"Correlation between morphological and functional retinal impairment in multiple sclerosis patients. Invest. Ophthalmol","volume":"40","author":"Parisi","year":"1999","journal-title":"Vis. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.msard.2018.03.007","article-title":"Optical coherence tomography as a biomarker of neurodegeneration in multiple sclerosis: A review","volume":"22","author":"Alonso","year":"2018","journal-title":"Mult. Scler. Relat. Disord."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"8503859","DOI":"10.1155\/2016\/8503859","article-title":"Optical Coherence Tomography as a Biomarker for Diagnosis, Progression, and Prognosis of Neurodegenerative Diseases","volume":"2016","author":"Satue","year":"2016","journal-title":"J. Ophthalmol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.pjnns.2017.10.009","article-title":"Optical coherence tomography in diagnosis and monitoring multiple sclerosis","volume":"52","author":"Kucharczuk","year":"2018","journal-title":"Neurol. Neurochir. Pol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1016\/S1474-4422(17)30278-8","article-title":"Retinal layer segmentation in multiple sclerosis: A systematic review and meta-analysis","volume":"16","author":"Petzold","year":"2017","journal-title":"Lancet. Neurol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1016\/j.ophtha.2005.10.040","article-title":"Relation of visual function to retinal nerve fiber layer thickness in multiple sclerosis","volume":"113","author":"Fisher","year":"2006","journal-title":"Ophthalmology"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1837","DOI":"10.1007\/s00415-017-8531-y","article-title":"Retinal ganglion cell analysis in multiple sclerosis and optic neuritis: A systematic review and meta-analysis","volume":"264","author":"Britze","year":"2017","journal-title":"J. Neurol."},{"key":"ref_22","first-page":"7361212","article-title":"Ability of Swept-Source Optical Coherence Tomography to Detect Retinal and Choroidal Changes in Patients with Multiple Sclerosis","volume":"2018","author":"Jarauta","year":"2018","journal-title":"J. Ophthalmol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"724","DOI":"10.1016\/j.nicl.2018.09.002","article-title":"Characterization of relapsing-remitting multiple sclerosis patients using support vector machine classifications of functional and diffusion MRI data","volume":"20","author":"Zurita","year":"2018","journal-title":"NeuroImage Clin."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Healy, B.C., Rotstein, D., Guttmann, C.R.G., Bakshi, R., Weiner, H.L., Brodley, C.E., and Chitnis, T. (2017). Exploration of machine learning techniques in predicting multiple sclerosis disease course. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0174866"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1177\/0037549716666962","article-title":"Comparison of machine learning methods for stationary wavelet entropy-based multiple sclerosis detection: Decision tree, k -nearest neighbors, and support vector machine","volume":"92","author":"Zhang","year":"2016","journal-title":"Simulation"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1002\/ana.22366","article-title":"Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria","volume":"69","author":"Polman","year":"2011","journal-title":"Ann. Neurol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"988","DOI":"10.1109\/72.788640","article-title":"An overview of statistical learning theory","volume":"10","author":"Vapnik","year":"1999","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1016\/0022-2496(75)90001-2","article-title":"The area above the ordinal dominance graph and the area below the receiver operating characteristic graph","volume":"12","author":"Bamber","year":"1975","journal-title":"J. Math. Psychol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1016\/0005-2795(75)90109-9","article-title":"Comparison of the predicted and observed secondary structure of T4 phage lysozyme","volume":"405","author":"Matthews","year":"1975","journal-title":"Biochim. Biophys. Acta-Protein Struct."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1186\/s13040-017-0155-3","article-title":"Ten quick tips for machine learning in computational biology","volume":"10","author":"Chicco","year":"2017","journal-title":"BioData Min."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/S1474-4422(17)30470-2","article-title":"Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria","volume":"17","author":"Thompson","year":"2018","journal-title":"Lancet Neurol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1080\/14737175.2019.1559051","article-title":"Novel uses of retinal imaging with optical coherence tomography in multiple sclerosis","volume":"19","author":"Oertel","year":"2019","journal-title":"Expert Rev. Neurother."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2021","DOI":"10.1016\/j.neuroimage.2012.05.078","article-title":"Classifying minimally disabled multiple sclerosis patients from resting state functional connectivity","volume":"62","author":"Richiardi","year":"2012","journal-title":"Neuroimage"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"47","DOI":"10.2147\/EB.S139417","article-title":"Retinal imaging with optical coherence tomography: A biomarker in multiple sclerosis?","volume":"10","author":"Costello","year":"2018","journal-title":"Eye Brain"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1111\/cxo.12858","article-title":"Optical coherence tomography in the investigation of systemic neurologic disease","volume":"102","author":"Srinivasan","year":"2019","journal-title":"Clin. Exp. Optom."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"884","DOI":"10.1038\/s41433-017-0010-2","article-title":"Optical coherence tomography in multiple sclerosis","volume":"32","author":"Britze","year":"2018","journal-title":"Eye"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"e628","DOI":"10.1111\/aos.12156","article-title":"Neural networks to identify multiple sclerosis with optical coherence tomography","volume":"91","author":"Pablo","year":"2013","journal-title":"Acta Ophthalmol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1016\/j.ophtha.2011.09.027","article-title":"Age and gender variations in age-related macular degeneration prevalence in populations of European ancestry: A meta-analysis","volume":"119","author":"Rudnicka","year":"2012","journal-title":"Ophthalmology"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1177\/1756285613488434","article-title":"Sex and gender issues in multiple sclerosis","volume":"6","author":"Harbo","year":"2013","journal-title":"Ther. Adv. Neurol. Disord."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Ribbons, K.A., McElduff, P., Boz, C., Trojano, M., Izquierdo, G., Duquette, P., Girard, M., Grand\u2019Maison, F., Hupperts, R., and Grammond, P. (2015). Male Sex Is Independently Associated with Faster Disability Accumulation in Relapse-Onset MS but Not in Primary Progressive MS. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0122686"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1310","DOI":"10.1002\/jnr.23019","article-title":"Estrogen treatment prevents gray matter atrophy in experimental autoimmune encephalomyelitis","volume":"90","author":"Rinek","year":"2012","journal-title":"J. Neurosci. Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jneuroim.2014.07.012","article-title":"Neuroimmune regulation of microglial activity involved in neuroinflammation and neurodegenerative diseases","volume":"274","author":"Elgueta","year":"2014","journal-title":"J. Neuroimmunol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"265","DOI":"10.3389\/fendo.2019.00265","article-title":"Autoimmune Disease in Women: Endocrine Transition and Risk Across the Lifespan","volume":"10","author":"Desai","year":"2019","journal-title":"Front. Endocrinol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.yfrne.2016.12.003","article-title":"Puberty and structural brain development in humans","volume":"44","author":"Herting","year":"2017","journal-title":"Front. Neuroendocrinol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"6504","DOI":"10.1167\/iovs.10-5551","article-title":"Tracking longitudinal retinal changes in experimental ocular hypertension using the cSLO and spectral domain-OCT","volume":"51","author":"Guo","year":"2010","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1469","DOI":"10.1016\/j.jocn.2011.04.008","article-title":"Reduced retinal nerve fiber layer and macular thickness in patients with multiple sclerosis with no history of optic neuritis identified by the use of spectral domain high-definition optical coherence tomography","volume":"18","author":"Fjeldstad","year":"2011","journal-title":"J. Clin. Neurosci."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1016\/j.ophtha.2013.09.035","article-title":"Retinal layer segmentation in patients with multiple sclerosis using spectral domain optical coherence tomography","volume":"121","author":"Polo","year":"2014","journal-title":"Ophthalmology"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1097\/IAE.0b013e3181bd2c3b","article-title":"Comparison of spectral\/Fourier domain optical coherence tomography instruments for assessment of normal macular thickness","volume":"30","author":"Sull","year":"2010","journal-title":"Retina"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1499","DOI":"10.1167\/iovs.16-20969","article-title":"Comparison Between Spectral-Domain and Swept-Source Optical Coherence Tomography Angiographic Imaging of Choroidal Neovascularization","volume":"58","author":"Miller","year":"2017","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Del Castillo, M.O., Cord\u00f3n, B., S\u00e1nchez Morla, E.M., Vilades, E., Rodrigo, M.J., Cavaliere, C., Boquete, L., and Garcia-Martin, E. (2019). Identification of clusters in multifocal electrophysiology recordings to maximize discriminant capacity (patients vs. control subjects). Doc. Ophthalmol.","DOI":"10.1007\/s10633-019-09720-8"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5323\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:39:44Z","timestamp":1760189984000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5323"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,3]]},"references-count":50,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["s19235323"],"URL":"https:\/\/doi.org\/10.3390\/s19235323","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,12,3]]}}}