{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:31:58Z","timestamp":1772555518569,"version":"3.50.1"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2022,1,7]],"date-time":"2022-01-07T00:00:00Z","timestamp":1641513600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,7]],"date-time":"2022-01-07T00:00:00Z","timestamp":1641513600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61762093"],"award-info":[{"award-number":["61762093"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007471","name":"Applied Basic Research Foundation of Yunnan Province","doi-asserted-by":"publisher","award":["2018FA036"],"award-info":[{"award-number":["2018FA036"]}],"id":[{"id":"10.13039\/100007471","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2022,7]]},"DOI":"10.1007\/s13042-021-01501-7","type":"journal-article","created":{"date-parts":[[2022,1,7]],"date-time":"2022-01-07T18:03:02Z","timestamp":1641578582000},"page":"1997-2011","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["3D transfer learning network for classification of Alzheimer\u2019s disease with MRI"],"prefix":"10.1007","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6370-8415","authenticated-orcid":false,"given":"Haifeng","family":"Wu","sequence":"first","affiliation":[]},{"given":"Jinling","family":"Luo","sequence":"additional","affiliation":[]},{"given":"Xiaoling","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Zeng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,7]]},"reference":[{"key":"1501_CR1","doi-asserted-by":"crossref","unstructured":"Abed MT, Fatema U, Nabil SA et al (2020) Alzheimer's disease prediction using convolutional neural network models leveraging pre-existing architecture and transfer learning. Joint 9th International Conference on Informatics, Electronics & Vision (ICIEV) and 2020 4th International Conference on Imaging, Vision & Pattern Recognition (icIVPR). IEEE, 1\u20136","DOI":"10.1109\/ICIEVicIVPR48672.2020.9306649"},{"issue":"2","key":"1501_CR2","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1016\/S1053-8119(02)00026-5","volume":"18","author":"G A\u00ebl Chetelat","year":"2003","unstructured":"A\u00ebl Chetelat G, Baron JC (2003) Early diagnosis of Alzheimer\u2019s disease: contribution of structural neuroimaging. Neuroimage 18(2):525\u2013541","journal-title":"Neuroimage"},{"key":"1501_CR3","first-page":"2","volume":"3","author":"I Arevalo-Rodriguez","year":"2015","unstructured":"Arevalo-Rodriguez I, Smailagic N, Figuls MR et al (2015) Mini-mental state examination (MMSE) for the detection of Alzheimer\u2019s disease and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 3:2","journal-title":"Cochrane Database Syst Rev"},{"key":"1501_CR4","first-page":"1","volume":"2","author":"A Ashraf","year":"2021","unstructured":"Ashraf A, Naz S, Shirazi SH et al (2021) Deep transfer learning for alzheimer neurological disorder detection. Multimed Tools Appl 2:1\u201326","journal-title":"Multimed Tools Appl"},{"key":"1501_CR6","doi-asserted-by":"publisher","first-page":"101645","DOI":"10.1016\/j.nicl.2018.101645","volume":"21","author":"S Basaia","year":"2019","unstructured":"Basaia S, Agosta F, Wagner L et al (2019) Automated classification of Alzheimer\u2019s disease and mild cognitive impairment using a single MRI and deep neural networks. NeuroImage Clin 21:101645","journal-title":"NeuroImage Clin"},{"issue":"10","key":"1501_CR7","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1016\/S1474-4422(03)00530-1","volume":"2","author":"K Blennow","year":"2003","unstructured":"Blennow K, Hampel H (2003) CSF markers for incipient Alzheimer\u2019s disease. Lancet Neurol 2(10):605\u2013613","journal-title":"Lancet Neurol"},{"key":"1501_CR8","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1016\/j.neuroimage.2015.01.048","volume":"111","author":"EE Bron","year":"2015","unstructured":"Bron EE, Smits M, Van Der Flier WM et al (2015) Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge. Neuroimage 111:562\u2013579","journal-title":"Neuroimage"},{"key":"1501_CR9","unstructured":"Chollet F (2015) Keras. https:\/\/keras.io\/."},{"key":"1501_CR10","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R et al (2009) Imagenet: a large-scale hierarchical image database. In 2009 IEEE conference on computer vision and pattern recognition. IEEE, pp. 248\u2013255","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"1501_CR11","first-page":"4","volume":"81","author":"MM Dessouky","year":"2013","unstructured":"Dessouky MM, Elrashidy MA, Abdelkader HM (2013) Selecting and extracting effective features for automated diagnosis of Alzheimer\u2019s disease. Int J Comput Appl 81:4","journal-title":"Int J Comput Appl"},{"key":"1501_CR12","doi-asserted-by":"crossref","unstructured":"Farooq A, Anwar S M, Awais M et al (2017) A deep CNN based multi-class classification of Alzheimer's disease using MRI. In 2017 IEEE International Conference on Imaging systems and techniques (IST). IEEE, pp. 1\u20136","DOI":"10.1109\/IST.2017.8261460"},{"key":"1501_CR13","doi-asserted-by":"publisher","first-page":"63605","DOI":"10.1109\/ACCESS.2019.2913847","volume":"7","author":"C Feng","year":"2019","unstructured":"Feng C, Elazab A, Yang P et al (2019) Deep learning framework for Alzheimer\u2019s disease diagnosis via 3D-CNN and FSBi-LSTM. IEEE Access 7:63605\u201363618","journal-title":"IEEE Access"},{"issue":"2","key":"1501_CR14","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1038\/nrneurol.2009.215","volume":"6","author":"GB Frisoni","year":"2010","unstructured":"Frisoni GB, Fox NC, Jack CR et al (2010) The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol 6(2):67\u201377","journal-title":"Nat Rev Neurol"},{"key":"1501_CR15","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.cmpb.2016.10.007","volume":"138","author":"XW Gao","year":"2017","unstructured":"Gao XW, Hui R, Tian Z (2017) Classification of CT brain images based on deep learning networks. Comput Methods Programs Biomed 138:49\u201356","journal-title":"Comput Methods Programs Biomed"},{"key":"1501_CR16","unstructured":"Glozman T, Liba O (2016) Hidden cues: Deep learning for Alzheimer's disease classification CS331B project final report"},{"issue":"9","key":"1501_CR17","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1001\/archneur.64.9.1323","volume":"64","author":"J Harrison","year":"2007","unstructured":"Harrison J, Minassian SL, Jenkins L et al (2007) A neuropsychological test battery for use in Alzheimer disease clinical trials. Arch Neurol 64(9):1323\u20131329","journal-title":"Arch Neurol"},{"key":"1501_CR18","doi-asserted-by":"crossref","unstructured":"Hon M, Khan N M (2017) Towards Alzheimer's disease classification through transfer learning. In 2017 IEEE International conference on bioinformatics and biomedicine (BIBM) (pp. 1166\u20131169). IEEE.","DOI":"10.1109\/BIBM.2017.8217822"},{"key":"1501_CR19","doi-asserted-by":"crossref","unstructured":"Hosseini-Asl E, Keynton R, El-Baz A (2016) Alzheimer's disease diagnostics by adaptation of 3D convolutional network. In 2016 IEEE International Conference on Image Processing (ICIP) (pp. 126\u2013130). IEEE.","DOI":"10.1109\/ICIP.2016.7532332"},{"key":"1501_CR20","unstructured":"Howard AG, Zhu M, Chen B et al (2017) Mobilenets: efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv: 1704.04861."},{"key":"1501_CR21","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.cogsys.2018.12.015","volume":"57","author":"R Jain","year":"2019","unstructured":"Jain R, Jain N, Aggarwal A et al (2019) Convolutional neural network based Alzheimer\u2019s disease classification from magnetic resonance brain images. Cogn Syst Res 57:147\u2013159","journal-title":"Cogn Syst Res"},{"issue":"4","key":"1501_CR22","doi-asserted-by":"publisher","first-page":"a006213","DOI":"10.1101\/cshperspect.a006213","volume":"2","author":"KA Johnson","year":"2012","unstructured":"Johnson KA, Fox NC, Sperling RA et al (2012) Brain imaging in Alzheimer disease. Cold Spring Harbor Perspect Med 2(4):a006213","journal-title":"Cold Spring Harbor Perspect Med"},{"issue":"2065","key":"1501_CR23","first-page":"20150202","volume":"374","author":"IT Jolliffe","year":"2016","unstructured":"Jolliffe IT, Cadima J (2016) Principal component analysis: a review and recent developments. Philos Trans R Soci Math Phys Eng Sci 374(2065):20150202","journal-title":"Philos Trans R Soci Math Phys Eng Sci"},{"issue":"5\u20136","key":"1501_CR24","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1159\/000084558","volume":"19","author":"KW Kim","year":"2005","unstructured":"Kim KW, Lee DY, Jhoo JH et al (2005) Diagnostic accuracy of mini-mental status examination and revised hasegawa dementia scale for Alzheimer\u2019s disease. Dement Geriatr Cogn Disord 19(5\u20136):324\u2013330","journal-title":"Dement Geriatr Cogn Disord"},{"issue":"2","key":"1501_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3383749","volume":"17","author":"SS Kumar","year":"2021","unstructured":"Kumar SS, Nandhini M (2021) Entropy slicing extraction and transfer learning classification for early diagnosis of Alzheimer diseases with sMRI. ACM Trans Multimed Comput Commun Appl 17(2):1\u201322","journal-title":"ACM Trans Multimed Comput Commun Appl"},{"issue":"1","key":"1501_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-37186-2","volume":"9","author":"G Lee","year":"2019","unstructured":"Lee G, Nho K, Kang B et al (2019) Predicting Alzheimer\u2019s disease progression using multi-modal deep learning approach. Sci Rep 9(1):1\u201312","journal-title":"Sci Rep"},{"issue":"4","key":"1501_CR27","doi-asserted-by":"publisher","first-page":"1132","DOI":"10.1109\/TBME.2014.2372011","volume":"62","author":"S Liu","year":"2014","unstructured":"Liu S, Liu S, Cai W et al (2014) Multimodal neuroimaging feature learning for multiclass diagnosis of Alzheimer\u2019s disease. IEEE Trans Biomed Eng 62(4):1132\u20131140","journal-title":"IEEE Trans Biomed Eng"},{"issue":"9","key":"1501_CR28","doi-asserted-by":"publisher","first-page":"1498","DOI":"10.1162\/jocn.2007.19.9.1498","volume":"19","author":"DS Marcus","year":"2007","unstructured":"Marcus DS, Wang TH, Parker J et al (2007) Open access series of imaging studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. J Cogn Neurosci 19(9):1498\u20131507","journal-title":"J Cogn Neurosci"},{"key":"1501_CR29","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.neuroscience.2021.01.002","volume":"460","author":"A Mehmood","year":"2021","unstructured":"Mehmood A, Yang S, Feng Z et al (2021) A transfer learning approach for early diagnosis of alzheimer\u2019s disease on MRI images. Neuroscience 460:43\u201352","journal-title":"Neuroscience"},{"issue":"4","key":"1501_CR30","doi-asserted-by":"publisher","first-page":"1140","DOI":"10.1016\/j.neubiorev.2012.01.004","volume":"36","author":"G Orru","year":"2012","unstructured":"Orru G, Pettersson-Yeo W, Marquand AF et al (2012) Using support vector machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review. Neurosci Biobehav Rev 36(4):1140\u20131152","journal-title":"Neurosci Biobehav Rev"},{"issue":"3","key":"1501_CR31","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1212\/WNL.0b013e3181cb3e25","volume":"74","author":"RC Petersen","year":"2010","unstructured":"Petersen RC, Aisen PS, Beckett LA et al (2010) Alzheimer\u2019s disease neuroimaging initiative (ADNI): clinical characterization. Neurology 74(3):201\u2013209","journal-title":"Neurology"},{"key":"1501_CR32","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1016\/j.neuroimage.2014.06.077","volume":"101","author":"HI Suk","year":"2014","unstructured":"Suk HI, Lee SW, Shen D et al (2014) Hierarchical feature representation and multimodal fusion with deep learning for AD\/MCI diagnosis. Neuroimage 101:569\u2013582","journal-title":"Neuroimage"},{"issue":"2","key":"1501_CR5","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.jalz.2013.02.003","volume":"9","author":"W Thies","year":"2013","unstructured":"Thies W, Bleiler L (2013) 2013 Alzheimer\u2019s disease facts and figures. Alzheimers Dement 9(2):208\u2013245","journal-title":"Alzheimers Dement"},{"issue":"5","key":"1501_CR33","doi-asserted-by":"publisher","first-page":"1073","DOI":"10.1007\/s10278-019-00265-5","volume":"33","author":"AB Tufail","year":"2020","unstructured":"Tufail AB, Ma YK, Zhang QN (2020) Binary classification of Alzheimer\u2019s disease using sMRI imaging modality and deep learning. J Digit Imaging 33(5):1073\u20131090","journal-title":"J Digit Imaging"},{"issue":"2","key":"1501_CR34","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1016\/j.neuroimage.2005.12.033","volume":"31","author":"L Wang","year":"2006","unstructured":"Wang L, Zang Y, He Y et al (2006) Changes in hippocampal connectivity in the early stages of Alzheimer\u2019s disease: evidence from resting state fMRI. Neuroimage 31(2):496\u2013504","journal-title":"Neuroimage"},{"issue":"10","key":"1501_CR35","doi-asserted-by":"publisher","first-page":"967","DOI":"10.1002\/hbm.20324","volume":"28","author":"K Wang","year":"2007","unstructured":"Wang K, Liang M, Wang L et al (2007) Altered functional connectivity in early Alzheimer\u2019s disease: A resting-state fMRI study. Hum Brain Mapp 28(10):967\u2013978","journal-title":"Hum Brain Mapp"},{"key":"1501_CR36","doi-asserted-by":"crossref","unstructured":"Yagis E, Citi L, Diciotti S et al (2020) 3D convolutional neural networks for diagnosis of Alzheimer\u2019s disease via structural MRI","DOI":"10.1109\/CBMS49503.2020.00020"},{"issue":"3","key":"1501_CR37","doi-asserted-by":"publisher","first-page":"856","DOI":"10.1016\/j.neuroimage.2011.01.008","volume":"55","author":"D Zhang","year":"2011","unstructured":"Zhang D, Wang Y, Zhou L et al (2011) Multimodal classification of Alzheimer\u2019s disease and mild cognitive impairment. Neuroimage 55(3):856\u2013867","journal-title":"Neuroimage"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-021-01501-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-021-01501-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-021-01501-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,22]],"date-time":"2023-01-22T07:54:03Z","timestamp":1674374043000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-021-01501-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,7]]},"references-count":37,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["1501"],"URL":"https:\/\/doi.org\/10.1007\/s13042-021-01501-7","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,7]]},"assertion":[{"value":"29 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 December 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}