{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T18:59:33Z","timestamp":1790276373176,"version":"4.1.0"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T00:00:00Z","timestamp":1762128000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100013013","name":"Target ALS","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013013","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001602","name":"Science Foundation Ireland","doi-asserted-by":"publisher","award":["20SP8953"],"award-info":[{"award-number":["20SP8953"]}],"id":[{"id":"10.13039\/501100001602","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001602","name":"Science Foundation Ireland","doi-asserted-by":"publisher","award":["NR-2024-NRG-S1"],"award-info":[{"award-number":["NR-2024-NRG-S1"]}],"id":[{"id":"10.13039\/501100001602","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","thelancet.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["eBioMedicine"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1016\/j.ebiom.2025.106029","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T08:59:07Z","timestamp":1763629147000},"page":"106029","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":5,"special_numbering":"C","title":["Dynamic modelling of the ALSFRS-R: leveraging population-based scores using neural networks"],"prefix":"10.1016","volume":"122","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7380-4219","authenticated-orcid":false,"given":"Robert","family":"McFarlane","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Ross","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"\u00c9anna Mac","family":"Domhnaill","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9579-5341","authenticated-orcid":false,"given":"Adriano","family":"Chi\u00f2","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philippe","family":"Corcia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caroline","family":"Ingre","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher J.","family":"McDermott","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M\u00f3nica Povedano","family":"Panad\u00e9s","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pamela J.","family":"Shaw","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4010-2357","authenticated-orcid":false,"given":"Philip","family":"van Damme","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leonard","family":"van den Berg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ammar","family":"Al-Chalabi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cathal","family":"Walsh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Orla","family":"Hardiman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ebiom.2025.106029_bib1","article-title":"Amyotrophic lateral sclerosis","volume":"3","author":"Hardiman","year":"2017","journal-title":"Nat Rev Dis Primers"},{"key":"10.1016\/j.ebiom.2025.106029_bib2","series-title":"The ALSFRS-R summit: a global call to action on the use of the ALSFRS-R in ALS clinical trials","author":"Genge","year":"2024"},{"issue":"1-2","key":"10.1016\/j.ebiom.2025.106029_bib3","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/S0022-510X(99)00210-5","article-title":"The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function","volume":"169","author":"Cedarbaum","year":"1999","journal-title":"J Neurol Sci"},{"issue":"5-6","key":"10.1016\/j.ebiom.2025.106029_bib4","doi-asserted-by":"crossref","first-page":"331","DOI":"10.3109\/21678421.2015.1026829","article-title":"A further rasch study confirms that ALSFRS-R does not conform to fundamental measurement requirements","volume":"16","author":"Franchignoni","year":"2015","journal-title":"Amyotroph Lateral Scler Frontotemporal Degener"},{"issue":"9","key":"10.1016\/j.ebiom.2025.106029_bib5","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1038\/s43588-022-00299-w","article-title":"Identifying patterns in amyotrophic lateral sclerosis progression from sparse longitudinal data","volume":"2","author":"Ramamoorthy","year":"2022","journal-title":"Nat Comput Sci"},{"issue":"4","key":"10.1016\/j.ebiom.2025.106029_bib6","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1109\/JBHI.2020.3019242","article-title":"A new dataset for facial motion analysis in individuals with neurological disorders","volume":"25","author":"Bandini","year":"2020","journal-title":"IEEE J Biomed Health Inform"},{"key":"10.1016\/j.ebiom.2025.106029_bib7","first-page":"1132","article-title":"Machine learning approaches in the detection of amyotrophic lateral sclerosis disease using orofacial gestures","volume":"3","author":"Macelaru","year":"2025"},{"issue":"1","key":"10.1016\/j.ebiom.2025.106029_bib8","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-022-17805-9","article-title":"Deep learning methods to predict amyotrophic lateral sclerosis disease progression","volume":"12","author":"Pancotti","year":"2022","journal-title":"Sci Rep"},{"key":"10.1016\/j.ebiom.2025.106029_bib9","first-page":"718","article-title":"Towards a machine learning empowered prognostic model for predicting disease progression for amyotrophic lateral sclerosis","volume":"2023","author":"Turabieh","year":"2023","journal-title":"AMIA Annu Symp Proc"},{"key":"10.1016\/j.ebiom.2025.106029_bib10","series-title":"2020 19th IEEE international conference on machine learning and applications (ICMLA)","article-title":"Domain adaptation from clinical trials data to the tertiary care clinic\u2013Application to ALS","year":"2020"},{"issue":"33-44","key":"10.1016\/j.ebiom.2025.106029_bib11","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1080\/21678421.2023.2285443","article-title":"Predicting amyotrophic lateral sclerosis (ALS) progression with machine learning","volume":"25","author":"Din Abdul Jabbar","year":"2024","journal-title":"Amyotroph Lateral Scler Frontotemporal Degener"},{"issue":"6","key":"10.1016\/j.ebiom.2025.106029_bib12","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1037\/h0042519","article-title":"The perceptron: a probabilistic model for information storage and organization in the brain","volume":"65","author":"Rosenblatt","year":"1958","journal-title":"Psychol Rev"},{"issue":"8","key":"10.1016\/j.ebiom.2025.106029_bib13","doi-asserted-by":"crossref","first-page":"10389","DOI":"10.1016\/j.eswa.2011.02.068","article-title":"Using artificial neural network models in stock market index prediction","volume":"38","author":"Guresen","year":"2011","journal-title":"Expert Syst Appl"},{"issue":"6677","key":"10.1016\/j.ebiom.2025.106029_bib14","doi-asserted-by":"crossref","first-page":"1416","DOI":"10.1126\/science.adi2336","article-title":"Learning skillful medium-range global weather forecasting","volume":"382","author":"Lam","year":"2023","journal-title":"Science"},{"key":"10.1016\/j.ebiom.2025.106029_bib15","doi-asserted-by":"crossref","first-page":"135","DOI":"10.3389\/fnins.2019.00135","article-title":"Machine learning in amyotrophic lateral sclerosis: achievements, pitfalls, and future directions","volume":"13","author":"Grollemund","year":"2019","journal-title":"Front Neurosci"},{"issue":"2","key":"10.1016\/j.ebiom.2025.106029_bib16","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1038\/s41582-020-00434-z","article-title":"Improving clinical trial outcomes in amyotrophic lateral sclerosis","volume":"17","author":"Kiernan","year":"2021","journal-title":"Nat Rev Neurol"},{"issue":"11","key":"10.1016\/j.ebiom.2025.106029_bib17","doi-asserted-by":"crossref","first-page":"1127","DOI":"10.1016\/S1474-4422(14)70129-2","article-title":"Clinical trials in amyotrophic lateral sclerosis: why so many negative trials and how can trials be improved?","volume":"13","author":"Mitsumoto","year":"2014","journal-title":"Lancet Neurol"},{"issue":"7","key":"10.1016\/j.ebiom.2025.106029_bib18","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1136\/jnnp-2016-314495","article-title":"The changing picture of amyotrophic lateral sclerosis: lessons from European registers","volume":"88","author":"Hardiman","year":"2017","journal-title":"J Neurol Neurosurg Psychiatry"},{"issue":"5-66","key":"10.1016\/j.ebiom.2025.106029_bib19","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1080\/21678421.2023.2215838","article-title":"Precision ALS\u2014an integrated pan European patient data platform for ALS","volume":"24","author":"McFarlane","year":"2023","journal-title":"Amyotroph Lateral Scler Frontotemporal Degener"},{"key":"10.1016\/j.ebiom.2025.106029_bib20","article-title":"Tensorflow: large-Scale machine learning on heterogeneous distributed systems","author":"Abadi","year":"2016","journal-title":"arXiv"},{"key":"10.1016\/j.ebiom.2025.106029_bib21","first-page":"2825","article-title":"Scikit-learn: machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J Mach Learn Res"},{"issue":"8","key":"10.1016\/j.ebiom.2025.106029_bib22","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput"},{"issue":"5-6","key":"10.1016\/j.ebiom.2025.106029_bib23","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1080\/07474938.2010.481556","article-title":"An empirical comparison of machine learning models for time series forecasting","volume":"29","author":"Ahmed","year":"2010","journal-title":"Econometric Rev"},{"key":"10.1016\/j.ebiom.2025.106029_bib24","article-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling","author":"Bai","year":"2018","journal-title":"arXiv"},{"key":"10.1016\/j.ebiom.2025.106029_bib25","doi-asserted-by":"crossref","first-page":"77996","DOI":"10.1109\/ACCESS.2018.2884647","article-title":"Data-driven air quality characterization for urban environments: a case study","volume":"6","author":"Zhou","year":"2018","journal-title":"IEEE Access"},{"key":"10.1016\/j.ebiom.2025.106029_bib26","first-page":"1","article-title":"Self-assessment of amyotrophic lateral sclerosis functional rating scale on the patient's smartphone proves to be non-inferior to clinic data capture","author":"Steinfurth","year":"2025","journal-title":"Amyotroph Lateral Scler Frontotemporal Degener"},{"issue":"5","key":"10.1016\/j.ebiom.2025.106029_bib27","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1002\/acn3.770","article-title":"Design and results of a smartphone-based digital phenotyping study to quantify ALS progression","volume":"6","author":"Berry","year":"2019","journal-title":"Ann Clin Transl Neurol"},{"key":"10.1016\/j.ebiom.2025.106029_bib28","series-title":"HomeSenseALS: a Mobile sensing and self-monitoring system to monitor patients with ALS in everyday life. ACM transactions on computing for healthcare","author":"Folgado","year":"2025"},{"issue":"1","key":"10.1016\/j.ebiom.2025.106029_bib29","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1186\/1477-7525-4-54","article-title":"Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change","volume":"4","author":"de Vet","year":"2006","journal-title":"Health Qual Life Outcomes"},{"issue":"4","key":"10.1016\/j.ebiom.2025.106029_bib30","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1016\/0197-2456(89)90005-6","article-title":"Measurement of health status: ascertaining the minimal clinically important difference","volume":"10","author":"Jaeschke","year":"1989","journal-title":"Control Clin Trials"},{"issue":"33-44","key":"10.1016\/j.ebiom.2025.106029_bib31","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1080\/21678421.2022.2153607","article-title":"Clinically meaningful change: evaluation of the Rasch-built overall amyotrophic lateral sclerosis disability scale (ROADS) and the ALSFRS-R","volume":"24","author":"Fournier","year":"2023","journal-title":"Amyotroph Lateral Scler Frontotemporal Degener"},{"issue":"5","key":"10.1016\/j.ebiom.2025.106029_bib32","doi-asserted-by":"crossref","first-page":"771","DOI":"10.1097\/WCO.0000000000000730","article-title":"Epidemiology of amyotrophic lateral sclerosis: an update of recent literature","volume":"32","author":"Longinetti","year":"2019","journal-title":"Curr Opin Neurol"},{"issue":"19","key":"10.1016\/j.ebiom.2025.106029_bib33","doi-asserted-by":"crossref","first-page":"e1905","DOI":"10.1212\/WNL.0000000000207797","article-title":"Epidemiologic trends of amyotrophic lateral sclerosis in Ireland, 1996\u20132021","volume":"101","author":"McFarlane","year":"2023","journal-title":"Neurology"},{"issue":"4","key":"10.1016\/j.ebiom.2025.106029_bib34","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1136\/jnnp.2009.183525","article-title":"Incidence of amyotrophic lateral sclerosis in Europe","volume":"81","author":"Logroscino","year":"2010","journal-title":"J Neurol Neurosurg Psychiatry"},{"issue":"7","key":"10.1016\/j.ebiom.2025.106029_bib35","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1136\/jnnp-2016-315018","article-title":"Genetic epidemiology of amyotrophic lateral sclerosis: a systematic review and meta-analysis","volume":"88","author":"Zou","year":"2017","journal-title":"J Neurol Neurosurg Psychiatry"},{"issue":"1","key":"10.1016\/j.ebiom.2025.106029_bib36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1162\/neco.1992.4.1.1","article-title":"Neural networks and the bias\/variance dilemma","volume":"4","author":"Geman","year":"1992","journal-title":"Neural Comput"},{"key":"10.1016\/j.ebiom.2025.106029_bib37","article-title":"Understanding deep learning requires rethinking generalization","author":"Zhang","year":"2016","journal-title":"arXiv"},{"key":"10.1016\/j.ebiom.2025.106029_bib38","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"Krizhevsky","year":"2012","journal-title":"Adv Neural Inf Process Syst"},{"key":"10.1016\/j.ebiom.2025.106029_bib39","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv"},{"issue":"2","key":"10.1016\/j.ebiom.2025.106029_bib40","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1212\/01.wnl.0000194316.91908.8a","article-title":"Progression rate of ALSFRS-R at time of diagnosis predicts survival time in ALS","volume":"66","author":"Kimura","year":"2006","journal-title":"Neurology"}],"container-title":["eBioMedicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2352396425004736?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2352396425004736?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T19:40:00Z","timestamp":1778874000000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2352396425004736"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":40,"alternative-id":["S2352396425004736"],"URL":"https:\/\/doi.org\/10.1016\/j.ebiom.2025.106029","relation":{},"ISSN":["2352-3964"],"issn-type":[{"value":"2352-3964","type":"print"}],"subject":[],"published":{"date-parts":[[2025,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Dynamic modelling of the ALSFRS-R: leveraging population-based scores using neural networks","name":"articletitle","label":"Article Title"},{"value":"eBioMedicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ebiom.2025.106029","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"106029"}}