{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T21:22:08Z","timestamp":1765228928587,"version":"3.46.0"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82204791"],"award-info":[{"award-number":["82204791"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2020A1515010002"],"award-info":[{"award-number":["2020A1515010002"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017594","name":"Medical Science and Technology Project of Zhejiang Province","doi-asserted-by":"publisher","award":["025A04J5526","2024A03J1067"],"award-info":[{"award-number":["025A04J5526","2024A03J1067"]}],"id":[{"id":"10.13039\/501100017594","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100020745","name":"Guangdong Provincial Key Laboratory Of Computational Science And Material Design","doi-asserted-by":"publisher","award":["B2024030"],"award-info":[{"award-number":["B2024030"]}],"id":[{"id":"10.13039\/501100020745","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Health Inf Sci Syst"],"DOI":"10.1007\/s13755-025-00407-w","type":"journal-article","created":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T19:18:30Z","timestamp":1765221510000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Utilizing multimodal models to forecast Alzheimer's disease progression and clinical subtypes"],"prefix":"10.1007","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1127-4608","authenticated-orcid":false,"given":"Hao","family":"Ren","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fengshi","family":"Jing","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zeyu","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Jin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lizhi","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,8]]},"reference":[{"key":"407_CR1","unstructured":"Prince M, Wimo A, Guerchet M, Ali G-C, Yu-Tzu W, Prina M. World Alzheimer Report 2015: The Global Impact of Dementia: an analysis of prevalence, incidence, cost and trends. London: Alzheimer\u2019s Disease International (ADI); 2015."},{"key":"407_CR2","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1159\/000109998","volume":"29","author":"BL Plassman","year":"2007","unstructured":"Plassman BL, Langa KM, Fisher GG, Heeringa SG, Weir DR, Ofstedal MB, et al. Prevalence of dementia in the United States: the aging, demographics, and memory study. Neuroepidemiology. 2007;29:125\u201332. https:\/\/doi.org\/10.1159\/000109998.","journal-title":"Neuroepidemiology"},{"key":"407_CR3","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1016\/S1474-4422(14)70090-0","volume":"13","author":"B Dubois","year":"2014","unstructured":"Dubois B, Feldman HH, Jacova C, Hampel H, Molinuevo JL, Blennow K, et al. Advancing research diagnostic criteria for Alzheimer\u2019s disease: the IWG-2 criteria. Lancet Neurol. 2014;13:614\u201329. https:\/\/doi.org\/10.1016\/S1474-4422(14)70090-0.","journal-title":"Lancet Neurol"},{"key":"407_CR4","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1176\/appi.focus.11.1.96","volume":"11","author":"MS Albert","year":"2013","unstructured":"Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, et al. The diagnosis of mild cognitive impairment due to Alzheimer\u2019s disease: recommendations from the National Institute on Aging-Alzheimer\u2019s Association workgroups on diagnostic guidelines for Alzheimer\u2019s disease. Focus (Madison). 2013;11:96\u2013106. https:\/\/doi.org\/10.1176\/appi.focus.11.1.96.","journal-title":"Focus (Madison)"},{"key":"407_CR5","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1002\/ana.21915","volume":"67","author":"MM Corrada","year":"2010","unstructured":"Corrada MM, Brookmeyer R, Paganini\u2010Hill A, Berlau D, Kawas CH. Dementia incidence continues to increase with age in the oldest old: the 90+ study. Ann Neurol. 2010;67:114\u201321. https:\/\/doi.org\/10.1002\/ana.21915.","journal-title":"Ann Neurol"},{"key":"407_CR6","doi-asserted-by":"publisher","first-page":"2112","DOI":"10.1016\/S0140-6736(05)67889-0","volume":"366","author":"CP Ferri","year":"2005","unstructured":"Ferri CP, Prince M, Brayne C, Brodaty H, Fratiglioni L, Ganguli M, et al. Global prevalence of dementia: a Delphi consensus study. Lancet. 2005;366:2112\u20137. https:\/\/doi.org\/10.1016\/S0140-6736(05)67889-0.","journal-title":"Lancet"},{"key":"407_CR7","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1002\/mds.25383","volume":"28","author":"GT Stebbins","year":"2013","unstructured":"Stebbins GT, Goetz CG, Burn DJ, Jankovic J, Khoo TK, Tilley BC. How to identify tremor dominant and postural instability\/gait difficulty groups with the movement disorder society unified Parkinson\u2019s disease rating scale: comparison with the unified Parkinson\u2019s disease rating scale. Mov Disord. 2013;28:668\u201370. https:\/\/doi.org\/10.1002\/mds.25383.","journal-title":"Mov Disord"},{"key":"407_CR8","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1007\/s00401-011-0889-9","volume":"123","author":"KA Jellinger","year":"2012","unstructured":"Jellinger KA. Neuropathological subtypes of Alzheimer\u2019s disease. Acta Neuropathol. 2012;123:153\u20134. https:\/\/doi.org\/10.1007\/s00401-011-0889-9.","journal-title":"Acta Neuropathol"},{"key":"407_CR9","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1016\/S1474-4422(11)70156-9","volume":"10","author":"ME Murray","year":"2011","unstructured":"Murray ME, Graff-Radford NR, Ross OA, Petersen RC, Duara R, Dickson DW. Neuropathologically defined subtypes of Alzheimer\u2019s disease with distinct clinical characteristics: a retrospective study. Lancet Neurol. 2011;10:785\u201396. https:\/\/doi.org\/10.1016\/S1474-4422(11)70156-9.","journal-title":"Lancet Neurol"},{"key":"407_CR10","doi-asserted-by":"publisher","first-page":"522","DOI":"10.1212\/WNL.35.4.522","volume":"35","author":"WJ Zetusky","year":"1985","unstructured":"Zetusky WJ, Jankovic J, Pirozzolo FJ. The heterogeneity of Parkinson\u2019s disease. Neurology. 1985;35:522\u2013522. https:\/\/doi.org\/10.1212\/WNL.35.4.522.","journal-title":"Neurology"},{"key":"407_CR11","doi-asserted-by":"publisher","first-page":"1529","DOI":"10.1212\/WNL.40.10.1529","volume":"40","author":"J Jankovic","year":"1990","unstructured":"Jankovic J, McDermott M, Carter J, Gauthier S, Goetz C, Golbe L, et al. Variable expression of Parkinson\u2019s disease. Neurology. 1990;40:1529\u20131529. https:\/\/doi.org\/10.1212\/WNL.40.10.1529.","journal-title":"Neurology"},{"key":"407_CR12","doi-asserted-by":"publisher","first-page":"e359","DOI":"10.1016\/S2589-7500(21)00274-0","volume":"4","author":"F Faghri","year":"2022","unstructured":"Faghri F, Brunn F, Dadu A, Zucchi E, Martinelli I, Mazzini L, et al. Identifying and predicting amyotrophic lateral sclerosis clinical subgroups: a population-based machine-learning study. Lancet Digit Health. 2022;4:e359\u201369. https:\/\/doi.org\/10.1016\/S2589-7500(21)00274-0.","journal-title":"Lancet Digit Health"},{"key":"407_CR13","doi-asserted-by":"publisher","first-page":"1307","DOI":"10.1016\/j.jalz.2017.04.011","volume":"13","author":"PK Crane","year":"2017","unstructured":"Crane PK, Trittschuh E, Mukherjee S, Saykin AJ, Sanders RE, Larson EB, et al. Incidence of cognitively defined late-onset Alzheimer\u2019s dementia subgroups from a prospective cohort study. Alzheimers Dement. 2017;13:1307\u201316. https:\/\/doi.org\/10.1016\/j.jalz.2017.04.011.","journal-title":"Alzheimers Dement"},{"key":"407_CR14","doi-asserted-by":"publisher","first-page":"2942","DOI":"10.1038\/s41380-018-0298-8","volume":"25","author":"S Mukherjee","year":"2020","unstructured":"Mukherjee S, Mez J, Trittschuh EH, Saykin AJ, Gibbons LE, Fardo DW, et al. Genetic data and cognitively defined late-onset Alzheimer\u2019s disease subgroups. Mol Psychiatry. 2020;25:2942\u201351. https:\/\/doi.org\/10.1038\/s41380-018-0298-8.","journal-title":"Mol Psychiatry"},{"key":"407_CR15","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.mcna.2018.10.009","volume":"103","author":"A Atri","year":"2019","unstructured":"Atri A. The Alzheimer\u2019s disease clinical spectrum. Med Clin North Am. 2019;103:263\u201393. https:\/\/doi.org\/10.1016\/j.mcna.2018.10.009.","journal-title":"Med Clin North Am"},{"key":"407_CR16","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1016\/S1474-4422(21)00066-1","volume":"20","author":"B Dubois","year":"2021","unstructured":"Dubois B, Villain N, Frisoni GB, Rabinovici GD, Sabbagh M, Cappa S, et al. Clinical diagnosis of Alzheimer\u2019s disease: recommendations of the International Working Group. Lancet Neurol. 2021;20:484\u201396. https:\/\/doi.org\/10.1016\/S1474-4422(21)00066-1.","journal-title":"Lancet Neurol"},{"key":"407_CR17","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1056\/NEJMoa1202753","volume":"367","author":"RJ Bateman","year":"2012","unstructured":"Bateman RJ, Xiong C, Benzinger TLS, Fagan AM, Goate A, Fox NC, et al. Clinical and biomarker changes in dominantly inherited Alzheimer\u2019s disease. N Engl J Med. 2012;367:795\u2013804. https:\/\/doi.org\/10.1056\/NEJMoa1202753.","journal-title":"N Engl J Med"},{"key":"407_CR18","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1016\/j.jalz.2011.03.003","volume":"7","author":"RA Sperling","year":"2011","unstructured":"Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of Alzheimer\u2019s disease: recommendations from the National Institute on Aging-Alzheimer\u2019s Association workgroups on diagnostic guidelines for Alzheimer\u2019s disease. Alzheimers Dement. 2011;7:280\u201392. https:\/\/doi.org\/10.1016\/j.jalz.2011.03.003.","journal-title":"Alzheimers Dement"},{"key":"407_CR19","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1016\/j.jalz.2018.02.018","volume":"14","author":"CR Jack","year":"2018","unstructured":"Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA research framework: toward a biological definition of Alzheimer\u2019s disease. Alzheimers Dement. 2018;14:535\u201362. https:\/\/doi.org\/10.1016\/j.jalz.2018.02.018.","journal-title":"Alzheimers Dement"},{"key":"407_CR20","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1016\/S1474-4422(12)70291-0","volume":"12","author":"CR Jack","year":"2013","unstructured":"Jack CR, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, et al. Tracking pathophysiological processes in Alzheimer\u2019s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12:207\u201316. https:\/\/doi.org\/10.1016\/S1474-4422(12)70291-0.","journal-title":"Lancet Neurol"},{"key":"407_CR21","doi-asserted-by":"publisher","DOI":"10.1186\/s13195-017-0283-5","volume":"9","author":"PS Aisen","year":"2017","unstructured":"Aisen PS, Cummings J, Jack CR, Morris JC, Sperling R, Fr\u00f6lich L, et al. On the path to 2025: understanding the Alzheimer\u2019s disease continuum. Alzheimers Res Ther. 2017;9:60. https:\/\/doi.org\/10.1186\/s13195-017-0283-5.","journal-title":"Alzheimers Res Ther"},{"key":"407_CR22","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.media.2018.05.004","volume":"48","author":"N Amoroso","year":"2018","unstructured":"Amoroso N, La Rocca M, Monaco A, Bellotti R, Tangaro S. Complex networks reveal early MRI markers of Parkinson\u2019s disease. Med Image Anal. 2018;48:12\u201324. https:\/\/doi.org\/10.1016\/j.media.2018.05.004.","journal-title":"Med Image Anal"},{"key":"407_CR23","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1016\/j.neuroimage.2017.03.057","volume":"155","author":"S Rathore","year":"2017","unstructured":"Rathore S, Habes M, Iftikhar MA, Shacklett A, Davatzikos C. A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer\u2019s disease and its prodromal stages. Neuroimage. 2017;155:530\u201348. https:\/\/doi.org\/10.1016\/j.neuroimage.2017.03.057.","journal-title":"Neuroimage"},{"key":"407_CR24","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1006\/nimg.2002.1132","volume":"17","author":"M Jenkinson","year":"2002","unstructured":"Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage. 2002;17:825\u201341. https:\/\/doi.org\/10.1006\/nimg.2002.1132.","journal-title":"Neuroimage"},{"key":"407_CR25","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/S1361-8415(01)00036-6","volume":"5","author":"M Jenkinson","year":"2001","unstructured":"Jenkinson M, Smith S. A global optimisation method for robust affine registration of brain images. Med Image Anal. 2001;5:143\u201356. https:\/\/doi.org\/10.1016\/S1361-8415(01)00036-6.","journal-title":"Med Image Anal"},{"key":"407_CR26","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1002\/hbm.10062","volume":"17","author":"SM Smith","year":"2002","unstructured":"Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17:143\u201355. https:\/\/doi.org\/10.1002\/hbm.10062.","journal-title":"Hum Brain Mapp"},{"key":"407_CR27","doi-asserted-by":"publisher","first-page":"14433","DOI":"10.1038\/s41598-023-41359-z","volume":"13","author":"J Zhang","year":"2023","unstructured":"Zhang J, Rao VM, Tian Y, Yang Y, Acosta N, Wan Z, et al. Detecting schizophrenia with 3D structural brain MRI using deep learning. Sci Rep. 2023;13:14433. https:\/\/doi.org\/10.1038\/s41598-023-41359-z.","journal-title":"Sci Rep"},{"key":"407_CR28","unstructured":"Chen S, Ma K, Zheng Y. Med3d: Transfer learning for 3d medical image analysis. arXiv preprint arXiv:190400625. 2019;"},{"key":"407_CR29","doi-asserted-by":"publisher","unstructured":"Li Y, Ding W, Wang X, Li L, Tang J. Alzheimer\u2019s Disease Classification Model Based on MED-3D Transfer Learning. In: Proceedings of the 2nd International Symposium on Artificial Intelligence for Medicine Sciences. New York, NY, USA: ACM; 2021. p. 394\u20138. https:\/\/doi.org\/10.1145\/3500931.3500999","DOI":"10.1145\/3500931.3500999"},{"key":"407_CR30","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.neucom.2023.01.012","volume":"529","author":"S Zhang","year":"2023","unstructured":"Zhang S, Li Z, Zhou H-Y, Ma J, Yu Y. Advancing 3D medical image analysis with variable dimension transform based supervised 3D pre-training. Neurocomputing. 2023;529:11\u201322. https:\/\/doi.org\/10.1016\/j.neucom.2023.01.012.","journal-title":"Neurocomputing"},{"key":"407_CR31","doi-asserted-by":"crossref","unstructured":"Satone VK, Kaur R, Dadu A, Leonard H, Iwaki H, Makarious M, et al. Predicting Alzheimer\u2019s disease progression trajectory and clinical subtypes using machine learning. bioRxiv. Cold Spring Harbor Laboratory; 2019;792432.","DOI":"10.1101\/792432"},{"key":"407_CR32","doi-asserted-by":"publisher","first-page":"695","DOI":"10.1111\/j.1532-5415.2005.53221.x","volume":"53","author":"ZS Nasreddine","year":"2005","unstructured":"Nasreddine ZS, Phillips NA, B\u00e9dirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53:695\u20139. https:\/\/doi.org\/10.1111\/j.1532-5415.2005.53221.x.","journal-title":"J Am Geriatr Soc"},{"key":"407_CR33","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1192\/S0007125000118082","volume":"145","author":"L Berg","year":"1984","unstructured":"Berg L. Clinical dementia rating. Br J Psychiatry. 1984;145:339\u2013339. https:\/\/doi.org\/10.1192\/S0007125000118082.","journal-title":"Br J Psychiatry"},{"key":"407_CR34","doi-asserted-by":"publisher","first-page":"1139","DOI":"10.1017\/S1041610214000295","volume":"26","author":"S Zaidi","year":"2014","unstructured":"Zaidi S, Kat MG, de Jonghe JFM. Clinician and caregiver agreement on neuropsychiatric symptom severity: a study using the Neuropsychiatric Inventory \u2013 Clinician rating scale (NPI-C). Int Psychogeriatr. 2014;26:1139\u201345. https:\/\/doi.org\/10.1017\/S1041610214000295.","journal-title":"Int Psychogeriatr"},{"key":"407_CR35","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1111\/j.1528-1157.1978.tb05041.x","volume":"19","author":"CB Dodrill","year":"1978","unstructured":"Dodrill CB. A neuropsychological battery for epilepsy. Epilepsia. 1978;19:611\u201323. https:\/\/doi.org\/10.1111\/j.1528-1157.1978.tb05041.x.","journal-title":"Epilepsia"},{"key":"407_CR36","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/0022-3956(75)90026-6","volume":"12","author":"MF Folstein","year":"1975","unstructured":"Folstein MF, Folstein SE, McHugh PR. \u201cMini-mental state\u201d: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res Pergamon. 1975;12:189\u201398.","journal-title":"J Psychiatr Res Pergamon"},{"key":"407_CR37","first-page":"165","volume-title":"Clinical gerontology","author":"JI Sheikh","year":"2014","unstructured":"Sheikh JI, Yesavage JA. Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. In: Brink TL, editor. Clinical gerontology. London: Routledge; 2014. p. 165\u201373."},{"key":"407_CR38","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1037\/0882-7974.14.4.627","volume":"14","author":"JC Allaire","year":"1999","unstructured":"Allaire JC, Marsiske M, American Psychological Association. Everyday cognition: age and intellectual ability correlates. Psychol Aging. 1999;14:627.","journal-title":"Psychol Aging"},{"key":"407_CR39","doi-asserted-by":"publisher","first-page":"2","DOI":"10.3102\/0013189X020003002","volume":"20","author":"G Salomon","year":"1991","unstructured":"Salomon G, Perkins DN, Globerson T. Partners in cognition: extending human intelligence with intelligent technologies. Educ Res. 1991;20:2\u20139. https:\/\/doi.org\/10.3102\/0013189X020003002.","journal-title":"Educ Res"},{"key":"407_CR40","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1093\/geronj\/36.4.428","volume":"36","author":"GG Fillenbaum","year":"1981","unstructured":"Fillenbaum GG, Smyer MA. The development, validity, and reliability of the Oars multidimensional functional assessment questionnaire. J Gerontol. 1981;36:428\u201334. https:\/\/doi.org\/10.1093\/geronj\/36.4.428.","journal-title":"J Gerontol"},{"key":"407_CR41","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1097\/00002093-199700112-00003","volume":"11","author":"RC Mohs","year":"1997","unstructured":"Mohs RC, Knopman D, Petersen RC, Ferris SH, Ernesto C, Grundman M, et al. Development of cognitive instruments for use in clinical trials of antidementia drugs: additions to the Alzheimer\u2019s Disease Assessment Scale that broaden its scope. Alzheimer Dis Assoc Disord LWW. 1997;11:13\u201321.","journal-title":"Alzheimer Dis Assoc Disord LWW"},{"key":"407_CR42","doi-asserted-by":"publisher","unstructured":"A new rating scale for Alzheimer\u2019s disease. American Journal of Psychiatry. 1984;141:1356\u201364. https:\/\/doi.org\/10.1176\/ajp.141.11.1356","DOI":"10.1176\/ajp.141.11.1356"},{"key":"407_CR43","doi-asserted-by":"publisher","first-page":"20150202","DOI":"10.1098\/rsta.2015.0202","volume":"374","author":"IT Jolliffe","year":"2016","unstructured":"Jolliffe IT, Cadima J. Principal component analysis: a review and recent developments. Philos Trans R Soc Lond A Math Phys Eng Sci. 2016;374:20150202. https:\/\/doi.org\/10.1098\/rsta.2015.0202.","journal-title":"Philos Trans R Soc Lond A Math Phys Eng Sci"},{"key":"407_CR44","first-page":"2579","volume":"9","author":"L van der Maaten","year":"2008","unstructured":"van der Maaten L, Hinton G. Visualizing data using t-SNE. J Mach Learn Res. 2008;9:2579\u2013605.","journal-title":"J Mach Learn Res"},{"key":"407_CR45","doi-asserted-by":"crossref","unstructured":"McInnes L, Healy J, Melville J. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. arXiv preprint arXiv:180203426. 2018;","DOI":"10.21105\/joss.00861"},{"key":"407_CR46","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Salakhutdinov RR. Reducing the dimensionality of data with neural networks. Science. 2006;313:504\u20137. https:\/\/doi.org\/10.1126\/science.1127647.","journal-title":"Science"},{"issue":"4","key":"407_CR47","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1126\/science.1127647","volume":"2","author":"H Abdi","year":"2010","unstructured":"Abdi H, Williams LJ. Principal component analysis. WIREs Comp Stats 2010;2(4):433\u201359.","journal-title":"WIREs Comp Stats"},{"key":"407_CR48","doi-asserted-by":"publisher","first-page":"2579","DOI":"10.1126\/science.1127647","volume":"9","author":"LV Maaten","year":"2008","unstructured":"Maaten LV, Hinton G. Visualizing data using t-SNE. J Mach Learn Res 2008;9:2579\u2013605.","journal-title":"J Mach Learn Res"},{"key":"407_CR49","doi-asserted-by":"publisher","unstructured":"McInnes L, Healy J, Melville J. Umap: Uniform manifold approximation and projection for dimension reduction. arXiv preprint https:\/\/doi.org\/10.48550\/arXiv.1802.03426. 2018 Feb 9","DOI":"10.48550\/arXiv.1802.03426"},{"issue":"5786","key":"407_CR50","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Salakhutdinov RR. Reducing the dimensionality of data with neural networks. Science. 2006 Jul 28;313(5786):504\u2013507. https:\/\/doi.org\/10.1126\/science.1127647","journal-title":"Science"}],"container-title":["Health Information Science and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13755-025-00407-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13755-025-00407-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13755-025-00407-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T19:18:32Z","timestamp":1765221512000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13755-025-00407-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,8]]},"references-count":50,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["407"],"URL":"https:\/\/doi.org\/10.1007\/s13755-025-00407-w","relation":{},"ISSN":["2047-2501"],"issn-type":[{"value":"2047-2501","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,8]]},"assertion":[{"value":"15 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"None declared.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The study was approved by the Ethics Committee of Guangdong Second Provincial General Hospital (2023-KY-KZ-287-02).","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"The study was approved by the Ethics Committee of Guangdong Second Provincial General Hospital (2023-KY-KZ-287-02).","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}}],"article-number":"10"}}