{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T01:35:08Z","timestamp":1785893708285,"version":"3.56.0"},"reference-count":21,"publisher":"IOP Publishing","issue":"9","license":[{"start":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T00:00:00Z","timestamp":1725580800000},"content-version":"vor","delay-in-days":5,"URL":"https:\/\/iopscience.iop.org\/page\/copyright"},{"start":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T00:00:00Z","timestamp":1725580800000},"content-version":"tdm","delay-in-days":5,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["U01NS077179"],"award-info":[{"award-number":["U01NS077179"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000894","name":"SMA foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000894","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100005202","name":"Muscular Dystrophy Association","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100005202","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004410","name":"TUBITAK","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004410","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100007721","name":"Cure SMA","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100007721","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Physiol. Meas."],"published-print":{"date-parts":[[2024,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>\n                  <jats:italic>Objective.<\/jats:italic> To evaluate electrical impedance myography (EIM) in conjunction with machine learning (ML) to detect infantile spinal muscular atrophy (SMA) and disease progression. <jats:italic>Approach<\/jats:italic>. Twenty-six infants with SMA and twenty-seven healthy infants had been enrolled and assessed with EIM as part of the NeuroNEXT SMA biomarker study. We applied a variety of modern, supervised ML approaches to this data, first seeking to differentiate healthy from SMA muscle, and then, using the best method, to track SMA progression. <jats:italic>Main Results.<\/jats:italic> Several of the ML algorithms worked well, but linear discriminant analysis (LDA) achieved 88.6% accuracy on subject muscles studied. This contrasts with a maximum of 60% accuracy that could be achieved using the single or multifrequency assessment approaches available at the time. LDA scores were also able to track progression effectively, although a multifrequency reactance-based measure also performed very well in this context. <jats:italic>Significance.<\/jats:italic> EIM enhanced with ML promises to be effective for providing effective diagnosis and tracking children and adults with SMA treated with currently available therapies. The normative trends identified here may also inform future applications of the technology in very young children. The basic analyses applied here could also likely be applied to other neuromuscular disorders characterized by muscle atrophy.<\/jats:p>","DOI":"10.1088\/1361-6579\/ad74d5","type":"journal-article","created":{"date-parts":[[2024,8,28]],"date-time":"2024-08-28T23:01:00Z","timestamp":1724886060000},"page":"095002","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Machine learning-enhanced electrical impedance myography to diagnose and track spinal muscular atrophy progression"],"prefix":"10.1088","volume":"45","author":[{"given":"Buket","family":"Sonbas Cobb","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen J","family":"Kolb","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6375-3312","authenticated-orcid":true,"given":"Seward B","family":"Rutkove","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2024,9,6]]},"reference":[{"key":"pmeaad74d5bib1","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.prrv.2023.06.004","article-title":"Evaluation of the therapeutic efficacy and tolerability of current drug treatments on the clinical outcomes of paediatric spinal muscular atrophy type 1: a systematic review","volume":"48","author":"Al-Taie","year":"2023","journal-title":"Paediatr. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2024-03-24","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2024-08-28","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2024-09-06","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}