{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T15:15:29Z","timestamp":1793891729827,"version":"4.8.0"},"reference-count":39,"publisher":"Elsevier BV","issue":"5","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,1,23]],"date-time":"2025-01-23T00:00:00Z","timestamp":1737590400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100019330","name":"Shanghai Clinical Research Center for Mental Health","doi-asserted-by":"publisher","award":["CRC2017ZD02"],"award-info":[{"award-number":["CRC2017ZD02"]}],"id":[{"id":"10.13039\/501100019330","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019330","name":"Shanghai Clinical Research Center for Mental Health","doi-asserted-by":"publisher","award":["19MC1911100"],"award-info":[{"award-number":["19MC1911100"]}],"id":[{"id":"10.13039\/501100019330","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People's Republic of China","doi-asserted-by":"publisher","award":["2009BAI77B03"],"award-info":[{"award-number":["2009BAI77B03"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People's Republic of China","doi-asserted-by":"publisher","award":["STI2030-Major Projects-2022ZD0213100"],"award-info":[{"award-number":["STI2030-Major Projects-2022ZD0213100"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People's Republic of China","doi-asserted-by":"publisher","award":["GWVI-11.2-XD24"],"award-info":[{"award-number":["GWVI-11.2-XD24"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82001123"],"award-info":[{"award-number":["82001123"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82101564"],"award-info":[{"award-number":["82101564"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82271607"],"award-info":[{"award-number":["82271607"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010031","name":"Postdoctoral Research Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010031","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2021M703340"],"award-info":[{"award-number":["2021M703340"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["BX2021333"],"award-info":[{"award-number":["BX2021333"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007279","name":"Shanghai Municipal Health Bureau","doi-asserted-by":"publisher","award":["GWV1\\u201311.2-XD24"],"award-info":[{"award-number":["GWV1\\u201311.2-XD24"]}],"id":[{"id":"10.13039\/501100007279","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Prevention of Alzheimer's Disease"],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1016\/j.tjpad.2025.100079","type":"journal-article","created":{"date-parts":[[2025,2,6]],"date-time":"2025-02-06T07:42:42Z","timestamp":1738827762000},"page":"100079","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":21,"title":["Predicting cognitive decline: Deep-learning reveals subtle brain changes in pre-MCI stage"],"prefix":"10.1016","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6476-0189","authenticated-orcid":false,"given":"Ling","family":"Yue","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongsheng","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-2739-6063","authenticated-orcid":false,"given":"Junyan","family":"Mao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5722-7847","authenticated-orcid":false,"given":"Bo","family":"Hong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Gu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingxia","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dinggang","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shifu","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.tjpad.2025.100079_bib0001","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1177\/1533317518791401","article-title":"Mild cognitive impairment in clinical practice: a review article","volume":"33","author":"Jongsiriyanyong","year":"2018","journal-title":"Am J Alzheimers Dis Other Demen"},{"key":"10.1016\/j.tjpad.2025.100079_bib0002","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1017\/S1092852918001347","article-title":"State of the science on mild cognitive impairment (MCI)","volume":"24","author":"Anderson","year":"2019","journal-title":"CNS Spectr"},{"key":"10.1016\/j.tjpad.2025.100079_bib0003","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1016\/j.cger.2013.07.009","article-title":"Risk factors for the progression of mild cognitive impairment to dementia","volume":"29","author":"Campbell","year":"2013","journal-title":"Clin Geriatr Med"},{"key":"10.1016\/j.tjpad.2025.100079_bib0004","doi-asserted-by":"crossref","first-page":"687","DOI":"10.2147\/CIA.S73922","article-title":"Mild cognitive impairment and its management in older people","volume":"10","author":"Eshkoor","year":"2015","journal-title":"Clin Interv Aging"},{"key":"10.1016\/j.tjpad.2025.100079_bib0005","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1111\/acps.12336","article-title":"Risk of dementia and mild cognitive impairment in older people with subjective memory complaints: meta-analysis","volume":"130","author":"Mitchell","year":"2014","journal-title":"Acta Psychiatr Scand"},{"key":"10.1016\/j.tjpad.2025.100079_bib0006","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/joim.12190","article-title":"Mild cognitive impairment: a concept in evolution","volume":"275","author":"Petersen","year":"2014","journal-title":"J Intern Med"},{"key":"10.1016\/j.tjpad.2025.100079_bib0007","doi-asserted-by":"crossref","DOI":"10.3389\/fcell.2022.1050769","article-title":"MCI-frcnn: a deep learning method for topological micro-domain boundary detection","volume":"10","author":"Tian","year":"2022","journal-title":"Front Cell Dev Biol"},{"key":"10.1016\/j.tjpad.2025.100079_bib0008","doi-asserted-by":"crossref","first-page":"3404","DOI":"10.1038\/s41467-022-31037-5","article-title":"Multimodal deep learning for Alzheimer's disease dementia assessment","volume":"13","author":"Qiu","year":"2022","journal-title":"Nat Commun"},{"key":"10.1016\/j.tjpad.2025.100079_bib0009","first-page":"293","article-title":"A novel deep learning framework on brain Functional networks for early MCI diagnosis","volume":"11072","author":"Kam","year":"2018","journal-title":"Med Image Comput Comput Assist Interv"},{"key":"10.1016\/j.tjpad.2025.100079_bib0010","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1186\/s12859-022-04946-x","article-title":"Deep multiview learning to identify imaging-driven subtypes in mild cognitive impairment","volume":"23","author":"Feng","year":"2022","journal-title":"BMC Bioinformatics"},{"key":"10.1016\/j.tjpad.2025.100079_bib0011","doi-asserted-by":"crossref","first-page":"2014","DOI":"10.1093\/jamia\/ocac168","article-title":"Multimodal attention-based deep learning for Alzheimer's disease diagnosis","volume":"29","author":"Golovanevsky","year":"2022","journal-title":"J Am Med Inform Assoc"},{"key":"10.1016\/j.tjpad.2025.100079_bib0012","doi-asserted-by":"crossref","first-page":"181","DOI":"10.3390\/brainsci10030181","article-title":"Multi-view based Multi-model learning for MCI diagnosis","volume":"10","author":"Cao","year":"2020","journal-title":"Brain Sci"},{"key":"10.1016\/j.tjpad.2025.100079_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.jneumeth.2020.108701","article-title":"Deep residual learning for neuroimaging: an application to predict progression to Alzheimer's disease","volume":"339","author":"Abrol","year":"2020","journal-title":"J Neurosci Methods"},{"key":"10.1016\/j.tjpad.2025.100079_bib0014","doi-asserted-by":"crossref","first-page":"1661","DOI":"10.3390\/genes12111661","article-title":"Pairwise correlation analysis of the Alzheimer's Disease neuroimaging initiative (ADNI) dataset reveals significant feature correlation","volume":"12","author":"Huckvale","year":"2021","journal-title":"Genes"},{"key":"10.1016\/j.tjpad.2025.100079_bib0015","first-page":"91","article-title":"Methodology of China's national study on the evaluation, early recognition, and treatment of psychological problems in the elderly: the China Longitudinal Aging Study (CLAS)","volume":"25","author":"Xiao","year":"2013","journal-title":"Shanghai Arch Psychiatry"},{"key":"10.1016\/j.tjpad.2025.100079_bib0016","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.media.2017.10.005","article-title":"Landmark-based deep multi-instance learning for brain disease diagnosis","volume":"43","author":"Liu","year":"2018","journal-title":"Med Image Anal"},{"key":"10.1016\/j.tjpad.2025.100079_bib0017","doi-asserted-by":"crossref","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":"10.1016\/j.tjpad.2025.100079_bib0018","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1002\/jmri.21049","article-title":"The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods","volume":"27","author":"Jack","year":"2008","journal-title":"J Magn Reson Imaging"},{"key":"10.1016\/j.tjpad.2025.100079_bib0019","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1212\/WNL.0000000000012587","article-title":"on behalf of the ADNI investigators. Amnestic MCI in ADNI","volume":"97","author":"Duff","year":"2021","journal-title":"Neurology"},{"key":"10.1016\/j.tjpad.2025.100079_bib0020","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/S0140-6736(20)30367-6","article-title":"Dementia prevention, intervention, and care: 2020 report of the Lancet Commission","volume":"396","author":"Livingston","year":"2020","journal-title":"Lancet"},{"issue":"5","key":"10.1016\/j.tjpad.2025.100079_bib39","doi-asserted-by":"crossref","first-page":"798","DOI":"10.1002\/hbm.20906","article-title":"The SRI24 multichannel atlas of normal adult human brain structure","volume":"31","author":"Rohlfing","year":"2010","journal-title":"Hum Brain Mapp"},{"key":"10.1016\/j.tjpad.2025.100079_bib0021","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1109\/TMI.2019.2928790","article-title":"Deep learning of static and dynamic brain functional networks for early MCI detection","volume":"39","author":"Kam","year":"2020","journal-title":"IEEE Trans Med Imaging"},{"key":"10.1016\/j.tjpad.2025.100079_bib0022","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.118048","article-title":"Suk H-I, and the Alzheimer's Disease Neuroimaging Initiative. A unified framework for personalized regions selection and functional relation modeling for early MCI identification","volume":"236","author":"Lee","year":"2021","journal-title":"Neuroimage"},{"key":"10.1016\/j.tjpad.2025.100079_bib0023","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/978-3-030-32622-7_8","article-title":"Multivariate data analysis and machine learning for prediction of MCI-to-AD conversion","volume":"1194","author":"Skolariki","year":"2020","journal-title":"Adv Exp Med Biol"},{"key":"10.1016\/j.tjpad.2025.100079_bib0024","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1016\/j.jalz.2019.02.007","article-title":"Alzheimer's Disease Neuroimaging Initiative and the Australian Imaging Biomarkers and Lifestyle Study of Aging. A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data","volume":"15","author":"Li","year":"2019","journal-title":"Alzheimers Dement"},{"key":"10.1016\/j.tjpad.2025.100079_bib0025","doi-asserted-by":"crossref","first-page":"4987","DOI":"10.1002\/alz.13083","article-title":"Comparing machine learning-derived MRI-based and blood-based neurodegeneration biomarkers in predicting syndromal conversion in early AD","volume":"19","author":"Cai","year":"2023","journal-title":"Alzheimers Dement"},{"key":"10.1016\/j.tjpad.2025.100079_bib0026","doi-asserted-by":"crossref","DOI":"10.1016\/j.arr.2022.101614","article-title":"Artificial intelligence in brain MRI analysis of Alzheimer's disease over the past 12 years: a systematic review","volume":"77","author":"Frizzell","year":"2022","journal-title":"Ageing Res Rev"},{"key":"10.1016\/j.tjpad.2025.100079_bib0027","doi-asserted-by":"crossref","first-page":"1933","DOI":"10.1098\/rspb.1998.0523","article-title":"Visual specialization and brain evolution in primates","volume":"265","author":"Barton","year":"1998","journal-title":"Proc Biol Sci"},{"key":"10.1016\/j.tjpad.2025.100079_bib0028","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1037\/0735-7036.120.1.31","article-title":"Amygdala size and hypothalamus size predict social play frequency in nonhuman primates: a comparative analysis using independent contrasts","volume":"120","author":"Lewis","year":"2006","journal-title":"J Comp Psychol"},{"key":"10.1016\/j.tjpad.2025.100079_bib0029","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.pscychresns.2011.06.014","article-title":"Alzheimer's Disease Neuroimaging Initiative. Amygdala atrophy is prominent in early Alzheimer's disease and relates to symptom severity","volume":"194","author":"Poulin","year":"2011","journal-title":"Psychiatry Res"},{"key":"10.1016\/j.tjpad.2025.100079_bib0030","doi-asserted-by":"crossref","first-page":"226","DOI":"10.3389\/fpsyt.2018.00226","article-title":"Asymmetry of hippocampus and amygdala defect in subjective cognitive decline among the community dwelling Chinese","volume":"9","author":"Yue","year":"2018","journal-title":"Front Psychiatry"},{"key":"10.1016\/j.tjpad.2025.100079_bib0031","doi-asserted-by":"crossref","first-page":"1055","DOI":"10.1002\/hipo.20573","article-title":"Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer's disease: meta-analyses of MRI studies","volume":"19","author":"Shi","year":"2009","journal-title":"Hippocampus"},{"key":"10.1016\/j.tjpad.2025.100079_bib0032","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.jns.2008.04.024","article-title":"Small baseline volume of left hippocampus is associated with subsequent conversion of MCI into dementia: the G\u00f6teborg MCI study","volume":"272","author":"Eckerstr\u00f6m","year":"2008","journal-title":"J. Neurol. Sci."},{"key":"10.1016\/j.tjpad.2025.100079_bib0033","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1016\/j.neurobiolaging.2014.10.041","article-title":"Relevance of parahippocampal-locus coeruleus connectivity to memory in early dementia","volume":"36","author":"Jacobs","year":"2015","journal-title":"Neurobiol Aging"},{"key":"10.1016\/j.tjpad.2025.100079_bib0034","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1007\/s12640-010-9175-1","article-title":"Progression of atrophy in Alzheimer's disease and related disorders","volume":"18","author":"Whitwell","year":"2010","journal-title":"Neurotox Res"},{"key":"10.1016\/j.tjpad.2025.100079_bib0035","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1111\/j.1749-6632.2000.tb06731.x","article-title":"The parahippocampal gyrus in Alzheimer's disease. Clinical and preclinical neuroanatomical correlates","volume":"911","author":"Van Hoesen","year":"2000","journal-title":"Ann N Y Acad Sci"},{"key":"10.1016\/j.tjpad.2025.100079_bib0036","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1007\/s00429-010-0283-8","article-title":"Atrophy in the parahippocampal gyrus as an early biomarker of Alzheimer's disease","volume":"215","author":"Ech\u00e1varri","year":"2011","journal-title":"Brain Struct Funct"},{"key":"10.1016\/j.tjpad.2025.100079_bib0037","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1093\/brain\/awx194","article-title":"The cerebellum in Alzheimer's disease: evaluating its role in cognitive decline","volume":"141","author":"Jacobs","year":"2018","journal-title":"Brain"},{"key":"10.1016\/j.tjpad.2025.100079_bib0038","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1089\/brain.2020.0937","article-title":"Hypermetabolic cerebellar connectome in Alzheimer's disease","volume":"13","author":"Gupta","year":"2023","journal-title":"Brain Connect"}],"container-title":["The Journal of Prevention of Alzheimer's Disease"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2274580725000238?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2274580725000238?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T13:39:38Z","timestamp":1786023578000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2274580725000238"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":39,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,5]]}},"alternative-id":["S2274580725000238"],"URL":"https:\/\/doi.org\/10.1016\/j.tjpad.2025.100079","relation":{},"ISSN":["2274-5807"],"issn-type":[{"value":"2274-5807","type":"print"}],"subject":[],"published":{"date-parts":[[2025,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Predicting cognitive decline: Deep-learning reveals subtle brain changes in pre-MCI stage","name":"articletitle","label":"Article Title"},{"value":"The Journal of Prevention of Alzheimer's Disease","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.tjpad.2025.100079","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 Masson SAS on behalf of SERDI Publisher.","name":"copyright","label":"Copyright"}],"article-number":"100079"}}