{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T10:01:04Z","timestamp":1792144864586,"version":"4.4.0"},"reference-count":25,"publisher":"SAGE Publications","issue":"12","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Mult Scler"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:sec>\n                    <jats:title>Background and Objectives:<\/jats:title>\n                    <jats:p>Multiple sclerosis (MS)-related disability is conventionally measured using the Expanded Disability Status Scale (EDSS), which requires neurological examination and is generally embedded in clinical records, making it unavailable in administrative datasets. This limits its utility for population-level estimates and healthcare planning. This study aims to use routinely collected healthcare data to fill this gap.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We conducted a population-based study using administrative data from Campania Region (Italy) to develop and validate neural network algorithms to estimate MS-related disability and predict its progression (2015\u20132021). We employed a deep learning approach to estimate the EDSS, and a hybrid model combining survival analysis with neural network predictions to forecast the risk of EDSS progression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>The model estimated EDSS with 0.68 accuracy, 0.68 precision, and 0.67 F1-score. The hybrid model had a predictive performance of 0.92. From 2016 to 2021, 9.01% of the population had EDSS \u2a7d 3.0, 62.10% had EDSS between 3.5 and 5.5, and 28.89% had EDSS \u2a7e 6.0. Looking at projections from 2021 to 2026, 67.68% people with EDSS \u2a7d 3.0 are expected to progress to EDSS 3.5\u20135.5.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>These findings highlight the potential of advanced data analytics using administrative data to improve MS monitoring, healthcare planning, and decision-making.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/13524585251347513","type":"journal-article","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T07:23:12Z","timestamp":1751527392000},"page":"1417-1426","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["Neural networks to estimate multiple sclerosis disability and predict progression using routinely collected healthcare data"],"prefix":"10.1177","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5416-0152","authenticated-orcid":false,"given":"Giuseppina","family":"Affinito","sequence":"first","affiliation":[{"name":"Department of Public Health, University of Naples Federico II, Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2613-3090","authenticated-orcid":false,"given":"Marcello","family":"Moccia","sequence":"additional","affiliation":[{"name":"Neurology Unit, Policlinico Federico II University Hospital, Naples, Italy"},{"name":"Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6388-8180","authenticated-orcid":false,"given":"Roberta","family":"Lanzillo","sequence":"additional","affiliation":[{"name":"Neurology Unit, Policlinico Federico II University Hospital, Naples, Italy"},{"name":"Department of Neuroscience, Reproductive Science and Odontostomatology, University of Naples Federico II, Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1855-5595","authenticated-orcid":false,"given":"Ruth Ann","family":"Marrie","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Dalhousie University, Halifax, NS, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeremy","family":"Chataway","sequence":"additional","affiliation":[{"name":"Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK"},{"name":"Medical Research Council Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK"},{"name":"Biomedical Research Centre, National Institute for Health Research, University College London Hospitals, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincenzo","family":"Brescia Morra","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Reproductive Science and Odontostomatology, University of Naples Federico II, Naples, Italy"},{"name":"Multiple Sclerosis Unit, Policlinico Federico II University Hospital, Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raffaele","family":"Palladino","sequence":"additional","affiliation":[{"name":"Department of Public Health, University of Naples Federico II, Naples, Italy"},{"name":"Department of Primary Care and Public Health, Imperial College, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,7,3]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41572-018-0041-4"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(18)30498-8"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awl007"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.33.11.1444"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2021.754144"},{"issue":"2","key":"e_1_3_2_7_2","article-title":"Validation of a machine learning approach to estimate Expanded Disability Status Scale scores for multiple sclerosis","volume":"8","author":"Alves P","year":"2022","unstructured":"Alves P, Green E, Leavy M, et al. Validation of a machine learning approach to estimate Expanded Disability Status Scale scores for multiple sclerosis. Mult Scler J Exp Transl Clin 2022; 8(2): 20552173221108635.","journal-title":"Mult Scler J Exp Transl Clin"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2023.1253557"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph15122796"},{"key":"e_1_3_2_10_2","unstructured":"Torje E Lundby B Rasheed A et al. Deep active learning for nonlinear system identification. https:\/\/arxiv.org\/abs\/2302.12667v1 (accessed June 14 2024)."},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-15805-z"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17103388"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.msard.2023.104585"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10072-023-07052-9"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1136\/jnnp-2018-319913"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000208051"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1177\/1352458515599075"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1177\/13524585221074010"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12874-018-0482-1"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2020.5842"},{"key":"e_1_3_2_21_2","volume-title":"3Rd International Conference on Learning Representations, ICLR 2015 \u2013 Conference Track Proceedings","author":"Kingma DP","unstructured":"Kingma DP, Ba JL. 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