{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T11:06:27Z","timestamp":1790420787962,"version":"4.1.0"},"reference-count":79,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100015747","name":"University Grants Commission","doi-asserted-by":"publisher","award":["3543\/(NET-DEC 2018)"],"award-info":[{"award-number":["3543\/(NET-DEC 2018)"]}],"id":[{"id":"10.13039\/100015747","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001843","name":"Science and Engineering Research Board","doi-asserted-by":"publisher","award":["EMR\/2017\/002294"],"award-info":[{"award-number":["EMR\/2017\/002294"]}],"id":[{"id":"10.13039\/501100001843","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007338","name":"All India Institute of Medical Sciences","doi-asserted-by":"crossref","award":["IEC-6\/2019"],"award-info":[{"award-number":["IEC-6\/2019"]}],"id":[{"id":"10.13039\/501100007338","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100007338","name":"All India Institute of Medical Sciences","doi-asserted-by":"crossref","award":["RP-43\/2019"],"award-info":[{"award-number":["RP-43\/2019"]}],"id":[{"id":"10.13039\/501100007338","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Spinocerebellar ataxia type 12 is a hereditary and neurodegenerative illness commonly found in India. However, there is no established noninvasive automatic diagnostic system for its diagnosis and identification of imaging biomarkers. This work proposes a novel four-phase machine learning\u2013based diagnostic framework to find spinocerebellar ataxia type 12 disease\u2013specific atrophic-brain regions and distinguish spinocerebellar ataxia type 12 from healthy using a real structural magnetic resonance imaging dataset. Firstly, each brain region is represented in terms of statistics of coefficients obtained using 3D-discrete wavelet transform. Secondly, a set of relevant regions are selected using a graph network\u2013based method. Thirdly, a kernel support vector machine is used to capture nonlinear relationships among the voxels of a brain region. Finally, the linear relationship among the brain regions is captured to build a decision model to distinguish spinocerebellar ataxia type 12 from healthy by using the regularized logistic regression method. A classification accuracy of 95% and a harmonic mean of precision and recall, i.e. F1-score of 94.92%, is achieved. The proposed framework provides relevant regions responsible for the atrophy. The importance of each region is captured using Shapley Additive exPlanations values. We also performed a statistical analysis to find volumetric changes in spinocerebellar ataxia type 12 group compared to healthy. The promising result of the proposed framework shows that clinicians can use it for early and timely diagnosis of spinocerebellar ataxia type 12.<\/jats:p>","DOI":"10.1093\/cercor\/bhae132","type":"journal-article","created":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T00:26:00Z","timestamp":1714350360000},"source":"Crossref","is-referenced-by-count":5,"title":["Integration of graph network with kernel SVM and logistic regression for identification of biomarkers in SCA12 and its diagnosis"],"prefix":"10.1093","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6520-5187","authenticated-orcid":false,"given":"Snigdha","family":"Agrawal","sequence":"first","affiliation":[{"name":"School of Computer and Systems Sciences, Jawaharlal Nehru University , New Mehrauli Road, New Delhi-110067 , India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3122-5096","authenticated-orcid":false,"given":"Ramesh Kumar","family":"Agrawal","sequence":"additional","affiliation":[{"name":"School of Computer and Systems Sciences, Jawaharlal Nehru University , New Mehrauli Road, New Delhi-110067 , India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4275-0139","authenticated-orcid":false,"given":"S Senthil","family":"Kumaran","sequence":"additional","affiliation":[{"name":"Department of NMR, All India Institute of Medical Sciences , Ansari Nagar, New Delhi-110029 , India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3788-6733","authenticated-orcid":false,"given":"Bharti","family":"Rana","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Delhi , Delhi-110007 , India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4590-7947","authenticated-orcid":false,"given":"Achal Kumar","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Department of Neurology, All India Institute of Medical Sciences , Ansari Nagar, New Delhi-110029 , India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,4,26]]},"reference":[{"issue":"12","key":"2024042900255561200_ref1","doi-asserted-by":"crossref","first-page":"2815","DOI":"10.1016\/j.neurobiolaging.2013.06.015","article-title":"How early can we predict Alzheimer\u2019s disease using computational anatomy?","volume":"34","author":"Adaszewski","year":"2013","journal-title":"Neurobiol Aging"},{"key":"2024042900255561200_ref2","first-page":"670","article-title":"Study of 2D feature extraction techniques for classification of spinocerebellar ataxia type 12 (SCA12)","volume":"290","author":"Agrawal","year":"2022","journal-title":"Stud Health Technol Inform"},{"issue":"1","key":"2024042900255561200_ref3","first-page":"91","article-title":"Fusion of 3D 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