{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T06:35:53Z","timestamp":1778222153531,"version":"3.51.4"},"reference-count":28,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2018,9,11]],"date-time":"2018-09-11T00:00:00Z","timestamp":1536624000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100003329","name":"Ministry of Economy and Competitiveness","doi-asserted-by":"publisher","award":["TEC2015-64718-R"],"award-info":[{"award-number":["TEC2015-64718-R"]}],"id":[{"id":"10.13039\/501100003329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006393","name":"University of Granada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006393","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007333","name":"Alzheimer\u2019s Disease Neuroimaging Initiative","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007333","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01 AG024904"],"award-info":[{"award-number":["U01 AG024904"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000005","name":"Department of Defense","doi-asserted-by":"publisher","award":["W81XWH-12-2-0012"],"award-info":[{"award-number":["W81XWH-12-2-0012"]}],"id":[{"id":"10.13039\/100000005","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100002565","name":"Alzheimer's Drug Discovery Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002565","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007742","name":"BioClinica","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007742","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100002491","name":"Bristol-Myers Squibb Company","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002491","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004312","name":"Eli Lilly and Company","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004312","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007013","name":"F. Hoffmann-La Roche","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007013","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005062","name":"Fujirebio","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006775","name":"GE Healthcare","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006775","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005205","name":"Janssen Research and Development","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005205","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007050","name":"Medpace","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007054","name":"Meso Scale Diagnostics","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004319","name":"Pfizer","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004319","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008272","name":"Novartis Pharmaceuticals","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008272","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009804","name":"Northern California Institute for Research and Education","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009804","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005595","name":"University of California","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005595","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1093\/jigpal\/jzy026","type":"journal-article","created":{"date-parts":[[2018,8,8]],"date-time":"2018-08-08T07:09:28Z","timestamp":1533712168000},"source":"Crossref","is-referenced-by-count":18,"title":["Using deep neural networks along with dimensionality reduction techniques to assist the diagnosis of neurodegenerative disorders"],"prefix":"10.1093","author":[{"given":"F","family":"Segovia","sequence":"first","affiliation":[{"name":"Department of Signal Theory, Networking and Communications, University of Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J M","family":"G\u00f3rriz","sequence":"additional","affiliation":[{"name":"Department of Signal Theory, Networking and Communications, University of Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J","family":"Ram\u00edrez","sequence":"additional","affiliation":[{"name":"Department of Signal Theory, Networking and Communications, University of Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"F J","family":"Martinez-Murcia","sequence":"additional","affiliation":[{"name":"Department of Signal Theory, Networking and Communications, University of Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M","family":"Garc\u00eda-P\u00e9rez","sequence":"additional","affiliation":[{"name":"Department of Signal Theory, Networking and Communications, University of Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,9,11]]},"reference":[{"key":"key\n\t\t\t\t20180911143312_C1","article-title":"TensorFlow: large-scale machine learning on heterogeneous systems","volume-title":"Software available from https:\/\/www.tensorflow.org\/","author":"Abadi"},{"key":"key\n\t\t\t\t20180911143312_C2","first-page":"1","article-title":"Classifiers in almost empty spaces","volume-title":"In 15th International Conference on Pattern Recognition","author":"Duin","year":"2000"},{"key":"key\n\t\t\t\t20180911143312_C3","doi-asserted-by":"crossref","first-page":"2616","DOI":"10.1093\/brain\/awm177","article-title":"FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer\u2019s disease","volume":"130","author":"Foster","year":"2007","journal-title":"Brain"},{"key":"key\n\t\t\t\t20180911143312_C4","volume-title":"Statistical Parametric Mapping: The Analysis of Functional Brain Images","author":"Friston","year":"2006"},{"key":"key\n\t\t\t\t20180911143312_C5","doi-asserted-by":"crossref","unstructured":"K. Friston and K.Stephan. Chapter 03 - Modelling brain responses. In Statistical Parametric Mapping, Karl Friston, John Ashburner, Stefan Kiebel, Thomas Nichols and William Penny, eds, pp. 32\u201345. Academic Press, London, 2007.","DOI":"10.1016\/B978-012372560-8\/50003-6"},{"key":"key\n\t\t\t\t20180911143312_C6","doi-asserted-by":"crossref","first-page":"670","DOI":"10.1212\/01.wnl.0000324625.00404.15","article-title":"Second consensus statement on the diagnosis of multiple system atrophy","volume":"71","author":"Gilman","year":"2008","journal-title":"Neurology"},{"key":"key\n\t\t\t\t20180911143312_C7","doi-asserted-by":"crossref","first-page":"11468","DOI":"10.1109\/ACCESS.2017.2714579","article-title":"Case-based statistical learning: a non-parametric implementation with a conditional-error rate SVM","volume":"5","author":"G\u00f3rriz","year":"2017","journal-title":"IEEE Access"},{"key":"key\n\t\t\t\t20180911143312_C8","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.eswa.2017.08.006","article-title":"A semi-supervised learning approach for model selection based on class-hypothesis testing","volume":"90","author":"Gorriz","year":"2017","journal-title":"Expert Systems with Applications"},{"key":"key\n\t\t\t\t20180911143312_C9","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1093\/brain\/awf080","article-title":"The accuracy of diagnosis of parkinsonian syndromes in a specialist movement disorder service","volume":"125","author":"Hughes","year":"2002","journal-title":"Brain"},{"key":"key\n\t\t\t\t20180911143312_C10","doi-asserted-by":"crossref","first-page":"5971","DOI":"10.1118\/1.4742055","article-title":"Automatic assistance to Parkinson\u2019s disease diagnosis in DaTSCAN SPECT imaging","volume":"39","author":"Ill\u00e1n","year":"2012","journal-title":"Medical Physics"},{"key":"key\n\t\t\t\t20180911143312_C11","first-page":"1109","article-title":"Clinical testing of an optimized software solution for an automated, observer-independent evaluation of dopamine transporter SPECT studies","volume":"46","author":"Koch","year":"2005","journal-title":"Journal of Nuclear Medicine: Official Publication, Society of Nuclear Medicine"},{"key":"key\n\t\t\t\t20180911143312_C12","doi-asserted-by":"crossref","first-page":"581","DOI":"10.2967\/jnumed.109.071811","article-title":"The value of the dopamine D2\/3 receptor ligand 18F-desmethoxyfallypride for the differentiation of idiopathic and nonidiopathic parkinsonian syndromes","volume":"51","author":"la Foug\u00e8re","year":"2010","journal-title":"Journal of Nuclear Medicine"},{"key":"key\n\t\t\t\t20180911143312_C13","doi-asserted-by":"crossref","first-page":"44565","DOI":"10.1038\/44565","article-title":"Learning the parts of objects by non-negative matrix factorization","volume":"401","author":"Lee","year":"1999","journal-title":"Nature"},{"key":"key\n\t\t\t\t20180911143312_C14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1212\/WNL.47.1.1","article-title":"Clinical research criteria for the diagnosis of progressive supranuclear palsy (Steele-Richardson-Olszewski syndrome): report of the NINDS-SPSP international workshop","volume":"47","author":"Litvan","year":"1996","journal-title":"Neurology"},{"key":"key\n\t\t\t\t20180911143312_C15","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1049\/el.2009.0176","article-title":"Automatic tool for alzheimer\u2019s disease diagnosis using PCA and bayesian classification rules","volume":"45","author":"Lopez","year":"2009","journal-title":"Electronics Letters"},{"key":"key\n\t\t\t\t20180911143312_C16","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1007\/978-3-319-59740-9_32","article-title":"A 3D convolutional neural network approach for the diagnosis of Parkinson\u2019s disease","volume-title":"Natural and Artificial Computation for Biomedicine and Neuroscience","author":"Martinez-Murcia","year":"2017"},{"key":"key\n\t\t\t\t20180911143312_C17","first-page":"439","article-title":"Naiad: a timely dataflow system. In Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles","author":"Murray","year":"2013"},{"key":"key\n\t\t\t\t20180911143312_C18","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.neulet.2010.05.047","article-title":"Analysis of SPECT brain images for the diagnosis of Alzheimer\u2019s disease based on NMF for feature extraction","volume":"479","author":"Padilla","year":"2010","journal-title":"Neuroscience Letters"},{"key":"key\n\t\t\t\t20180911143312_C19","article-title":"pharmaceutical and bioinformatics applications. International Journal of Molecular Sciences","volume-title":"Deep artificial neural networks and neuromorphic chips for big data analysis","author":"Pastur-Romay","year":"2016"},{"key":"key\n\t\t\t\t20180911143312_C20","first-page":"2825","article-title":"Scikit-learn: machine learning in Python","volume-title":"Journal of Machine Learning Research","author":"Pedregosa","year":"2011"},{"key":"key\n\t\t\t\t20180911143312_C21","first-page":"623","article-title":"An automatic threshold-based scaling method for enhancing the usefulness of Tc-HMPAO SPECT in the diagnosis of Alzheimer\u2019s disease","author":"Saxena","year":"1998"},{"key":"key\n\t\t\t\t20180911143312_C22","doi-asserted-by":"crossref","unstructured":"F. Segovia , C.Bastin, E.Salmon, J. M.G\u00f3rriz, J.Ram\u00edrez and C.Phillips. Combining PET images and neuropsychological test data for automatic diagnosis of Alzheimer's disease. In PLoS ONE, 9, e88687, 2014. doi:10.1371\/journal.pone.0088687.","DOI":"10.1371\/journal.pone.0088687"},{"key":"key\n\t\t\t\t20180911143312_C23","first-page":"101342B","article-title":"Analysis of 18F-DMFP-PET data using hidden Markov random field and the Gaussian distribution to assist the diagnosis of Parkinsonism","volume-title":"Proceeding of SPIE Medical Imaging 2017","author":"Segovia"},{"key":"key\n\t\t\t\t20180911143312_C24","doi-asserted-by":"crossref","DOI":"10.3389\/fninf.2017.00023","article-title":"Multivariate analysis of 18F-DMFP PET data to assist the diagnosis of Parkinsonism","volume-title":"Frontiers in Neuroinformatics","author":"Segovia","year":"2017"},{"key":"key\n\t\t\t\t20180911143312_C25","article-title":"TensorFlow","volume-title":"Google\u2019s latest machine learning system, open sourced for everyone"},{"key":"key\n\t\t\t\t20180911143312_C26","first-page":"699","article-title":"Automatic classification of 123I-FP-CIT (DaTSCAN) SPECT images","volume-title":"Nuclear Medicine Communications","author":"Towey","year":"2011"},{"key":"key\n\t\t\t\t20180911143312_C27","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1177\/155005941104200304","article-title":"Improving Alzheimer\u2019s disease diagnosis with machine learning techniques","volume":"42","author":"Trambaiolli","year":"2011","journal-title":"Clinical EEG and Neuroscience"},{"key":"key\n\t\t\t\t20180911143312_C28","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1162\/jocn.1991.3.1.71","article-title":"Eigenfaces for recognition","volume":"3","author":"Turk","year":"1991","journal-title":"Journal of Cognitive Neuroscience"}],"container-title":["Logic Journal of the IGPL"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/jigpal\/advance-article-pdf\/doi\/10.1093\/jigpal\/jzy026\/25715531\/jzy026.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T20:49:25Z","timestamp":1571690965000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jigpal\/advance-article\/doi\/10.1093\/jigpal\/jzy026\/5092720"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,11]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1093\/jigpal\/jzy026","relation":{},"ISSN":["1367-0751","1368-9894"],"issn-type":[{"value":"1367-0751","type":"print"},{"value":"1368-9894","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,11]]}}}