{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T11:07:34Z","timestamp":1725534454375},"reference-count":54,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2020,6,11]],"date-time":"2020-06-11T00:00:00Z","timestamp":1591833600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neuroinform."],"DOI":"10.3389\/fninf.2020.00025","type":"journal-article","created":{"date-parts":[[2020,6,11]],"date-time":"2020-06-11T05:10:15Z","timestamp":1591852215000},"update-policy":"http:\/\/dx.doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":79,"title":["A Machine Learning Approach for the Differential Diagnosis of Alzheimer and Vascular Dementia Fed by MRI Selected Features"],"prefix":"10.3389","volume":"14","author":[{"given":"Gloria","family":"Castellazzi","sequence":"first","affiliation":[]},{"given":"Maria Giovanna","family":"Cuzzoni","sequence":"additional","affiliation":[]},{"given":"Matteo","family":"Cotta Ramusino","sequence":"additional","affiliation":[]},{"given":"Daniele","family":"Martinelli","sequence":"additional","affiliation":[]},{"given":"Federica","family":"Denaro","sequence":"additional","affiliation":[]},{"given":"Antonio","family":"Ricciardi","sequence":"additional","affiliation":[]},{"given":"Paolo","family":"Vitali","sequence":"additional","affiliation":[]},{"given":"Nicoletta","family":"Anzalone","sequence":"additional","affiliation":[]},{"given":"Sara","family":"Bernini","sequence":"additional","affiliation":[]},{"given":"Fulvia","family":"Palesi","sequence":"additional","affiliation":[]},{"given":"Elena","family":"Sinforiani","sequence":"additional","affiliation":[]},{"given":"Alfredo","family":"Costa","sequence":"additional","affiliation":[]},{"given":"Giuseppe","family":"Micieli","sequence":"additional","affiliation":[]},{"given":"Egidio","family":"D'Angelo","sequence":"additional","affiliation":[]},{"given":"Giovanni","family":"Magenes","sequence":"additional","affiliation":[]},{"given":"Claudia A. M.","family":"Gandini Wheeler-Kingshott","sequence":"additional","affiliation":[]}],"member":"1965","published-online":{"date-parts":[[2020,6,11]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/0165-1684(95)00041-B","article-title":"Radial basis function and related models: an overview","volume":"45","author":"Acosta","year":"1995","journal-title":"Signal Process."},{"key":"B2","doi-asserted-by":"publisher","first-page":"1877","DOI":"10.1093\/brain\/aww083","article-title":"Thalamic pathology and memory loss in early Alzheimer's disease: moving the focus from the medial temporal lobe to Papez circuit","volume":"139","author":"Aggleton","year":"2016","journal-title":"Brain"},{"key":"B3","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/s10072-016-2764-x","article-title":"Advanced magnetic resonance imaging of neurodegenerative diseases","volume":"38","author":"Agosta","year":"2017","journal-title":"Neurol. Sci."},{"key":"B4","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/j.neuroimage.2017.04.014","article-title":"Human brain mapping: a systematic comparison of parcellation methods for the human cerebral cortex","volume":"170","author":"Arslan","year":"2018","journal-title":"Neuroimage"},{"key":"B5","first-page":"327","article-title":"Vascular dementia: pharmacological treatment approaches and perspectives","volume":"2","author":"Baskys","year":"2007","journal-title":"Clin. Interv. Aging"},{"key":"B6","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1007\/s10072-008-0970-x","article-title":"Twenty years after Spinnler and Tognoni: new instruments in the Italian neuropsychologist's toolbox","volume":"29","author":"Bianchi","year":"2008","journal-title":"Neurol. Sci."},{"key":"B7","volume-title":"Pattern Recognition and Machine Learning","author":"Bishop","year":"2006"},{"key":"B8","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1212\/WNL.0000000000004059","article-title":"Functional network integrity presages cognitive decline in preclinical Alzheimer disease","volume":"89","author":"Buckley","year":"2017","journal-title":"Neurology"},{"key":"B9","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1159\/000117297","article-title":"The Mental Deterioration Battery: normative data, diagnostic reliability and qualitative analyses of cognitive impairment. The Group for the Standardization of the Mental Deterioration Battery","volume":"36","author":"Carlesimo","year":"1996","journal-title":"Eur. Neurol."},{"key":"B10","doi-asserted-by":"publisher","first-page":"223","DOI":"10.3389\/fnins.2014.00223","article-title":"A comprehensive assessment of resting state networks: bidirectional modification of functional integrity in cerebro-cerebellar networks in dementia","volume":"8","author":"Castellazzi","year":"2014","journal-title":"Front. Neurosci."},{"key":"B11","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"B12","doi-asserted-by":"publisher","first-page":"e0179804","DOI":"10.1371\/journal.pone.0179804","article-title":"Machine learning and microsimulation techniques on the prognosis of dementia: a systematic literature review","volume":"12","author":"Dallora","year":"2017","journal-title":"PLoS ONE"},{"key":"B13","doi-asserted-by":"publisher","first-page":"169","DOI":"10.3233\/JAD-161120","article-title":"Functional disintegration of the default mode network in prodromal Alzheimer's disease","volume":"59","author":"Dillen","year":"2017","journal-title":"J. Alzheimers Dis."},{"key":"B14","doi-asserted-by":"publisher","first-page":"2118","DOI":"10.1002\/hbm.22759","article-title":"Multimodal analysis of functional and structural disconnection in Alzheimer's disease using multiple kernel SVM","volume":"36","author":"Dyrba","year":"2015","journal-title":"Hum. Brain Mapp."},{"key":"B15","doi-asserted-by":"publisher","first-page":"351","DOI":"10.2214\/ajr.149.2.351","article-title":"MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging","volume":"149","author":"Fazekas","year":"1987","journal-title":"AJR Am. J. Roentgenol."},{"key":"B16","doi-asserted-by":"publisher","first-page":"657","DOI":"10.3389\/fnins.2019.00657","article-title":"Resting state dynamic functional connectivity in neurodegenerative conditions: a review of magnetic resonance imaging findings","volume":"13","author":"Filippi","year":"2019","journal-title":"Front. Neurosci."},{"key":"B17","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/0022-3956(75)90026-6","article-title":"\u201cMini-mental state\u201d. A practical method for grading the cognitive state of patients for the clinician","volume":"12","author":"Folstein","year":"1975","journal-title":"J. Psychiatr Res."},{"key":"B18","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1109\/72.143376","article-title":"A constructive method for multivariate function approximation by multilayer perceptrons","volume":"3","author":"Geva","year":"1992","journal-title":"IEEE Trans. Neural Netw."},{"key":"B19","volume-title":"Deep Learning","author":"Goodfellow","year":"2016"},{"key":"B20","doi-asserted-by":"publisher","first-page":"4637","DOI":"10.1073\/pnas.0308627101","article-title":"Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI","volume":"101","author":"Greicius","year":"2004","journal-title":"Proc. Natl. Acad. Sci. U.S.A."},{"key":"B21","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1176\/jnp.12.3.305","article-title":"Vascular dementia and Alzheimer's disease: is there a difference? A comparison of symptoms by disease duration","volume":"12","author":"Groves","year":"2000","journal-title":"J. Neuropsychiatry Clin. Neurosci."},{"key":"B22","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1001\/archneur.1975.00490510088009","article-title":"Cerebral blood flow in dementia","volume":"32","author":"Hachinski","year":"1975","journal-title":"Arch. Neurol."},{"key":"B23","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1148\/radiology.143.1.7063747","article-title":"The meaning and use of the area under a receiver operating characteristic (ROC) curve","volume":"143","author":"Hanley","year":"1982","journal-title":"Radiology"},{"key":"B24","volume-title":"Neural Networks: A Comprehensive Foundation","author":"Haykin","year":"1998"},{"key":"B25","doi-asserted-by":"crossref","first-page":"445","DOI":"10.31887\/DCNS.2013.15.4\/hjahn","article-title":"Memory loss in Alzheimer's disease","volume":"15","author":"Jahn","year":"2013","journal-title":"Dialogues Clin. Neurosci."},{"key":"B26","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1023\/a:1008280620621","article-title":"Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF","volume":"7","author":"Kononenko","year":"1997","journal-title":"Appl. Intell."},{"key":"B27","doi-asserted-by":"publisher","first-page":"77","DOI":"10.3389\/fnagi.2016.00077","article-title":"Discriminative learning for Alzheimer's disease diagnosis via canonical correlation analysis and multimodal fusion","volume":"8","author":"Lei","year":"2016","journal-title":"Front. Aging Neurosci."},{"key":"B28","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1016\/j.neuroimage.2013.09.015","article-title":"Inter-modality relationship constrained multi-modality multi-task feature selection for Alzheimer's Disease and mild cognitive impairment identification","volume":"84","author":"Liu","year":"2014","journal-title":"Neuroimage"},{"key":"B29","doi-asserted-by":"publisher","first-page":"1305","DOI":"10.1002\/hbm.22254","article-title":"Hierarchical fusion of features and classifier decisions for Alzheimer's disease diagnosis","volume":"35","author":"Liu","year":"2014","journal-title":"Hum. Brain Mapp."},{"key":"B30","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.trsl.2018.01.001","article-title":"Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease","volume":"194","author":"Liu","year":"2018","journal-title":"Transl. Res."},{"key":"B31","doi-asserted-by":"publisher","first-page":"e0173372","DOI":"10.1371\/journal.pone.0173372","article-title":"Prediction and classification of Alzheimer disease based on quantification of MRI deformation","volume":"12","author":"Long","year":"2017","journal-title":"PLoS ONE"},{"key":"B32","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.jalz.2011.03.005","article-title":"The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease","volume":"7","author":"McKhann","year":"2011","journal-title":"Alzheimers Dement."},{"key":"B33","doi-asserted-by":"publisher","first-page":"S37","DOI":"10.1007\/s10072-006-0545-7","article-title":"Vascular dementia","volume":"27","author":"Micieli","year":"2006","journal-title":"Neurol. Sci."},{"key":"B34","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1212\/WNL.49.4.1096","article-title":"Meta-analysis of the Hachinski Ischemic Score in pathologically verified dementias","volume":"49","author":"Moroney","year":"1997","journal-title":"Neurology"},{"key":"B35","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1002\/(SICI)1097-0258(19980430)17:8<873::AID-SIM779>3.0.CO;2-I","article-title":"Interval estimation for the difference between independent proportions: comparison of eleven methods","volume":"17","author":"Newcombe","year":"1998","journal-title":"Stat. Med."},{"key":"B36","doi-asserted-by":"publisher","first-page":"274","DOI":"10.3389\/fnins.2018.00274","article-title":"Specific patterns of white matter alterations help distinguishing Alzheimer's and vascular dementia","volume":"12","author":"Palesi","year":"2018","journal-title":"Front. Neurosci."},{"key":"B37","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1016\/j.dadm.2018.07.004","article-title":"Machine learning of neuroimaging for assisted diagnosis of cognitive impairment and dementia: a systematic review","volume":"10","author":"Pellegrini","year":"2018","journal-title":"Alzheimers Dement."},{"key":"B38","doi-asserted-by":"publisher","first-page":"8","DOI":"10.3389\/fnagi.2019.00008","article-title":"Evaluation of functional decline in Alzheimer's dementia using 3D deep learning and group ICA for rs-fMRI measurements","volume":"11","author":"Qureshi","year":"2019","journal-title":"Front. Aging Neurosci."},{"key":"B39","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1038\/nrneurol.2011.2","article-title":"Epidemiology of Alzheimer disease","volume":"7","author":"Reitz","year":"2011","journal-title":"Nat. Rev. Neurol."},{"key":"B40","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1002\/widm.2","article-title":"Robust statistics for outlier detection","volume":"1","author":"Rousseeuw","year":"2011","journal-title":"WIREs Data Min. Knowl. Discov."},{"key":"B41","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1016\/j.neuroimage.2009.10.003","article-title":"Complex network measures of brain connectivity: uses and interpretations","volume":"52","author":"Rubinov","year":"2010","journal-title":"Neuroimage"},{"key":"B42","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","article-title":"Learning representations by back-propagating errors","volume":"323","author":"Rumelhart","year":"1986","journal-title":"Nature"},{"key":"B43","article-title":"Learning internal representations by error propagation","volume-title":"Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations","author":"Rumelhart","year":"1987"},{"key":"B44","doi-asserted-by":"publisher","first-page":"a006189","DOI":"10.1101\/cshperspect.a006189","article-title":"Neuropathological alterations in Alzheimer disease","volume":"1","author":"Serrano-Pozo","year":"2011","journal-title":"Cold Spring Harb. Perspect. Med."},{"key":"B45","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1093\/cercor\/bhr099","article-title":"Decoding subject-driven cognitive states with whole-brain connectivity patterns","volume":"22","author":"Shirer","year":"2012","journal-title":"Cereb. Cortex"},{"key":"B46","doi-asserted-by":"publisher","first-page":"1487","DOI":"10.1016\/j.neuroimage.2006.02.024","article-title":"Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data","volume":"31","author":"Smith","year":"2006","journal-title":"Neuroimage"},{"key":"B47","doi-asserted-by":"publisher","first-page":"69","DOI":"10.3233\/JAD-131829","article-title":"Fractional anisotropy changes in Alzheimer's disease depend on the underlying fiber tract architecture: a multiparametric DTI study using joint independent component analysis","volume":"41","author":"Teipel","year":"2014","journal-title":"J. Alzheimers Dis."},{"key":"B48","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1006\/nimg.2001.0978","article-title":"Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain","volume":"15","author":"Tzourio-Mazoyer","year":"2002","journal-title":"Neuroimage"},{"key":"B49","doi-asserted-by":"publisher","first-page":"2712","DOI":"10.1161\/STROKEAHA.107.513176","article-title":"Progression of cerebral small vessel disease in relation to risk factors and cognitive consequences: Rotterdam Scan study","volume":"39","author":"van Dijk","year":"2008","journal-title":"Stroke"},{"key":"B50","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1016\/j.biopsych.2017.08.010","article-title":"Anti-amyloid-\u03b2 monoclonal antibodies for Alzheimer's disease: pitfalls and promise","volume":"83","author":"van Dyck","year":"2018","journal-title":"Biol. Psychiatry"},{"key":"B51","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1111\/nan.12472","article-title":"Review: vascular dementia: clinicopathologic and genetic considerations","volume":"44","author":"Vinters","year":"2018","journal-title":"Neuropathol. Appl. Neurobiol."},{"key":"B52","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/0165-0114(78)90029-5","article-title":"Fuzzy sets as a basis for a theory of possibility","volume":"1","author":"Zadeh","year":"1978","journal-title":"Fuzzy Sets Syst."},{"key":"B53","doi-asserted-by":"publisher","first-page":"856","DOI":"10.1016\/j.neuroimage.2011.01.008","article-title":"Multimodal classification of Alzheimer's disease and mild cognitive impairment","volume":"55","author":"Zhang","year":"2011","journal-title":"Neuroimage"},{"key":"B54","doi-asserted-by":"publisher","first-page":"1097","DOI":"10.3389\/fneur.2019.01097","article-title":"Machine learning-based framework for differential diagnosis between vascular dementia and Alzheimer's disease using structural MRI features","volume":"10","author":"Zheng","year":"2019","journal-title":"Front. Neurol."}],"container-title":["Frontiers in Neuroinformatics"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/article\/10.3389\/fninf.2020.00025\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,19]],"date-time":"2021-03-19T21:13:04Z","timestamp":1616188384000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/article\/10.3389\/fninf.2020.00025\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,11]]},"references-count":54,"alternative-id":["10.3389\/fninf.2020.00025"],"URL":"https:\/\/doi.org\/10.3389\/fninf.2020.00025","relation":{},"ISSN":["1662-5196"],"issn-type":[{"value":"1662-5196","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,11]]}}}