{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T20:43:28Z","timestamp":1793825008899,"version":"4.6.1"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T00:00:00Z","timestamp":1746489600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T00:00:00Z","timestamp":1746489600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-025-97674-0","type":"journal-article","created":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T14:50:46Z","timestamp":1746543046000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["MINDSETS: Multi-omics Integration with Neuroimaging for Dementia Subtyping and Effective Temporal Study"],"prefix":"10.1038","volume":"15","author":[{"given":"Salma","family":"Hassan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dawlat","family":"Akaila","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryam","family":"Arjemandi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vijay","family":"Papineni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Yaqub","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,5,6]]},"reference":[{"key":"97674_CR1","unstructured":"WHO. World health organization: Dementia key factors (2023). https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/dementia."},{"key":"97674_CR2","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.trsl.2022.12.003","volume":"254","author":"LB Eisenmenger","year":"2023","unstructured":"Eisenmenger, L. B. et al. Vascular contributions to Alzheimer\u2019s disease. Transl. Res. 254, 41\u201353 (2023).","journal-title":"Transl. Res."},{"key":"97674_CR3","unstructured":"for Disease Control, C. & (CDC), P. Alzheimer\u2019s disease and related dementias. https:\/\/www.cdc.gov\/aging\/aginginfo\/alzheimers.htm."},{"key":"97674_CR4","unstructured":"Rajkumar, A.\u00a0P. et al. Delirium, dementia, and other cognitive disorders. New Oxford Textbook of Psychiatry 371 (2020)."},{"key":"97674_CR5","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1016\/j.procs.2020.09.071","volume":"176","author":"RB Ammar","year":"2020","unstructured":"Ammar, R. B. & Ayed, Y. B. Language-related features for early detection of Alzheimer disease. Procedia Comput. Sci. 176, 763\u2013770 (2020).","journal-title":"Procedia Comput. Sci."},{"key":"97674_CR6","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1001\/jama.2019.17421","volume":"323","author":"CM Borelli","year":"2020","unstructured":"Borelli, C. M., Grennan, D. & Muth, C. C. Causes of memory loss in elderly persons. JAMA 323, 486\u2013486 (2020).","journal-title":"JAMA"},{"key":"97674_CR7","doi-asserted-by":"publisher","first-page":"1763","DOI":"10.3233\/JAD-210322","volume":"81","author":"JA Hirsch","year":"2021","unstructured":"Hirsch, J. A. et al. Expanded exploration of the auditory naming test in patients with dementia. J. Alzheimer\u2019s Dis. 81, 1763\u20131779 (2021).","journal-title":"J. Alzheimer\u2019s Dis."},{"key":"97674_CR8","doi-asserted-by":"crossref","unstructured":"Kim, Y.\u00a0H., Kwon, O.\u00a0D. et al. Clinical correlates of hachinski ischemic score and vascular factors in cognitive function of elderly. BioMed Res. Int. 2014 (2014).","DOI":"10.1155\/2014\/852784"},{"key":"97674_CR9","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.neuropharm.2017.12.030","volume":"134","author":"RN Kalaria","year":"2018","unstructured":"Kalaria, R. N. The pathology and pathophysiology of vascular dementia. Neuropharmacology 134, 226\u2013239 (2018).","journal-title":"Neuropharmacology"},{"key":"97674_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12883-014-0183-2","volume":"14","author":"I Arevalo-Rodriguez","year":"2014","unstructured":"Arevalo-Rodriguez, I. et al. Diagnostic tools for Alzheimer\u2019s disease dementia and other dementias: An overview of diagnostic test accuracy (dta) systematic reviews. BMC Neurol. 14, 1\u20138 (2014).","journal-title":"BMC Neurol."},{"key":"97674_CR11","doi-asserted-by":"publisher","first-page":"365","DOI":"10.3390\/diagnostics14040365","volume":"14","author":"Y-C Ni","year":"2024","unstructured":"Ni, Y.-C. et al. Classification prediction of Alzheimer\u2019s disease and vascular dementia using physiological data and ecd spect images. Diagnostics 14, 365 (2024).","journal-title":"Diagnostics"},{"key":"97674_CR12","doi-asserted-by":"crossref","unstructured":"Sokolovi\u010d, L., Hofmann, M.\u00a0J., Mohammad, N. & Kukolja, J. Neuropsychological differential diagnosis of Alzheimer\u2019s disease and vascular dementia: A systematic review with meta-regressions. Front. Aging Neurosci. 15 (2023).","DOI":"10.3389\/fnagi.2023.1267434"},{"key":"97674_CR13","doi-asserted-by":"publisher","first-page":"1355","DOI":"10.1017\/S1041610217000096","volume":"29","author":"N Arnaoutoglou","year":"2017","unstructured":"Arnaoutoglou, N. et al. Color perception differentiates Alzheimer\u2019s disease (ad) from vascular dementia (vad) patients. Int. Psychogeriatr. 29, 1355\u20131361 (2017).","journal-title":"Int. Psychogeriatr."},{"key":"97674_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12916-014-0206-2","volume":"12","author":"J Attems","year":"2014","unstructured":"Attems, J. & Jellinger, K. A. The overlap between vascular disease and Alzheimer\u2019s disease-lessons from pathology. BMC Med. 12, 1\u201312 (2014).","journal-title":"BMC Med."},{"key":"97674_CR15","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1161\/01.STR.0000054050.51530.76","volume":"34","author":"C Iadecola","year":"2003","unstructured":"Iadecola, C. & Gorelick, P. B. Converging pathogenic mechanisms in vascular and neurodegenerative dementia. Stroke 34, 335\u2013337 (2003).","journal-title":"Stroke"},{"key":"97674_CR16","doi-asserted-by":"publisher","first-page":"1097","DOI":"10.3389\/fneur.2019.01097","volume":"10","author":"Y Zheng","year":"2019","unstructured":"Zheng, Y. et al. Machine learning-based framework for differential diagnosis between vascular dementia and Alzheimer\u2019s disease using structural mri features. Front. Neurol. 10, 1097 (2019).","journal-title":"Front. Neurol."},{"key":"97674_CR17","unstructured":"Chouliaras, L. & O\u2019Brien, J.\u00a0T. The use of neuroimaging techniques in the early and differential diagnosis of dementia. Mol. Psychiatry 1\u201314 (2023)."},{"key":"97674_CR18","first-page":"676","volume":"19","author":"R Ghai","year":"2020","unstructured":"Ghai, R. et al. Current strategies and novel drug approaches for Alzheimer disease. CNS Neurol. Disord.-Drug Targets (Formerly Current Drug Targets-CNS & Neurological Disorders) 19, 676\u2013690 (2020).","journal-title":"CNS Neurol. Disord.-Drug Targets (Formerly Current Drug Targets-CNS & Neurological Disorders)"},{"key":"97674_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.jstrokecerebrovasdis.2021.105864","volume":"30","author":"SC Bir","year":"2021","unstructured":"Bir, S. C., Khan, M. W., Javalkar, V., Toledo, E. G. & Kelley, R. E. Emerging concepts in vascular dementia: A review. J. Stroke Cerebrovasc. Dis. 30, 105864 (2021).","journal-title":"J. Stroke Cerebrovasc. Dis."},{"key":"97674_CR20","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1038\/s41467-020-14373-2","volume":"11","author":"F Llorens","year":"2020","unstructured":"Llorens, F. et al. Cerebrospinal fluid lipocalin 2 as a novel biomarker for the differential diagnosis of vascular dementia. Nat. Commun. 11, 619 (2020).","journal-title":"Nat. Commun."},{"key":"97674_CR21","doi-asserted-by":"publisher","first-page":"908","DOI":"10.1002\/alz.12091","volume":"16","author":"IF J\u00f8rgensen","year":"2020","unstructured":"J\u00f8rgensen, I. F., Aguayo-Orozco, A., Lademann, M. & Brunak, S. Age-stratified longitudinal study of Alzheimer\u2019s and vascular dementia patients. Alzheimer\u2019s Dement. 16, 908\u2013917 (2020).","journal-title":"Alzheimer\u2019s Dement."},{"key":"97674_CR22","unstructured":"Manouvelou, S. et al. Differential diagnosis of Alzheimer\u2019s disease and vascular dementia using visual rating scales. Hell. J. Radiol. 5 (2020)."},{"key":"97674_CR23","doi-asserted-by":"publisher","DOI":"10.3233\/jad-231071","author":"S Ottaviani","year":"2024","unstructured":"Ottaviani, S. & Monacelli, F. Rethinking dementia risk prediction: A critical evaluation of a multimodal machine learning predictive model. J. Alzheimer\u2019s Dis. JAD https:\/\/doi.org\/10.3233\/jad-231071 (2024).","journal-title":"J. Alzheimer\u2019s Dis. JAD"},{"key":"97674_CR24","doi-asserted-by":"publisher","DOI":"10.1002\/alz.074628","volume":"19","author":"D Vaghari","year":"2023","unstructured":"Vaghari, D. et al. Validating the clinical utility of ai-guided tools for early dementia prediction. Alzheimer\u2019s Dement. 19, e074628 (2023).","journal-title":"Alzheimer\u2019s Dement."},{"key":"97674_CR25","doi-asserted-by":"publisher","DOI":"10.1002\/alz.083130","volume":"19","author":"AJ Cirincione","year":"2023","unstructured":"Cirincione, A. J. et al. Prediction of future dementia for mci patients using a novel multimodal machine learning framework. Alzheimer\u2019s Dement. 19, e083130 (2023).","journal-title":"Alzheimer\u2019s Dement."},{"key":"97674_CR26","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0294253","volume":"18","author":"S Jahan","year":"2023","unstructured":"Jahan, S. et al. Explainable ai-based Alzheimer\u2019s prediction and management using multimodal data. Plos One 18, e0294253 (2023).","journal-title":"Plos One"},{"key":"97674_CR27","doi-asserted-by":"publisher","DOI":"10.3233\/jad-230496","author":"H Ding","year":"2023","unstructured":"Ding, H. et al. Multimodal machine learning for 10-year dementia risk prediction: The framingham heart study. J. Alzheimer\u2019s Dis. JAD https:\/\/doi.org\/10.3233\/jad-230496 (2023).","journal-title":"J. Alzheimer\u2019s Dis. JAD"},{"key":"97674_CR28","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1007\/978-3-319-67389-9_16","volume":"10541","author":"T Zhou","year":"2017","unstructured":"Zhou, T., Thung, K.-H., Zhu, X. & Shen, D. Feature learning and fusion of multimodality neuroimaging and genetic data for multi-status dementia diagnosis. Mach. Learn. Med. Imaging MLMI 10541, 132\u2013140. https:\/\/doi.org\/10.1007\/978-3-319-67389-9_16 (2017).","journal-title":"Mach. Learn. Med. Imaging MLMI"},{"key":"97674_CR29","doi-asserted-by":"publisher","DOI":"10.3233\/JAD-220021","author":"G Mirabnahrazam","year":"2022","unstructured":"Mirabnahrazam, G. et al. Machine learning based multimodal neuroimaging genomics dementia score for predicting future conversion to Alzheimer\u2019s disease. J. Alzheimer\u2019s Dis. JAD https:\/\/doi.org\/10.3233\/JAD-220021 (2022).","journal-title":"J. Alzheimer\u2019s Dis. JAD"},{"key":"97674_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102789","volume":"86","author":"B Billot","year":"2023","unstructured":"Billot, B. et al. Synthseg: Segmentation of brain mri scans of any contrast and resolution without retraining. Med. Image Anal. 86, 102789 (2023).","journal-title":"Med. Image Anal."},{"key":"97674_CR31","doi-asserted-by":"crossref","unstructured":"Sadil, P. & Lindquist, M.\u00a0A. Comparing automated subcortical volume estimation methods; amygdala volumes estimated by fsl and freesurfer have poor consistency. Tech. Rep., Wiley Online Library (2024).","DOI":"10.1101\/2024.03.07.583900"},{"key":"97674_CR32","doi-asserted-by":"publisher","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","volume":"77","author":"JJ Van Griethuysen","year":"2017","unstructured":"Van Griethuysen, J. J. et al. Computational radiomics system to decode the radiographic phenotype. Cancer Res. 77, e104\u2013e107 (2017).","journal-title":"Cancer Res."},{"key":"97674_CR33","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1097\/MOG.0000000000000966","volume":"39","author":"L Yao","year":"2023","unstructured":"Yao, L. et al. A review of deep learning and radiomics approaches for pancreatic cancer diagnosis from medical imaging. Curr. Opin. Gastroenterol. 39, 436\u2013447 (2023).","journal-title":"Curr. Opin. Gastroenterol."},{"key":"97674_CR34","unstructured":"Szabo, L. et al. Radiomics of pericardial fat: a new frontier in heart failure discrimination and prediction. Eur. Radiol. 1\u201314 (2023)."},{"key":"97674_CR35","doi-asserted-by":"publisher","first-page":"423","DOI":"10.3233\/JAD-200948","volume":"79","author":"C Birkenbihl","year":"2021","unstructured":"Birkenbihl, C. et al. Anmerge: A comprehensive and accessible Alzheimer\u2019s disease patient-level dataset. J. Alzheimer\u2019s Dis. 79, 423\u2013431 (2021).","journal-title":"J. Alzheimer\u2019s Dis."},{"key":"97674_CR36","doi-asserted-by":"crossref","unstructured":"Akiba, T., Sano, S., Yanase, T., Ohta, T. & Koyama, M. Optuna: A next-generation hyperparameter optimization framework. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2623\u20132631 (2019).","DOI":"10.1145\/3292500.3330701"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-97674-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-97674-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-97674-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,11]],"date-time":"2025-05-11T03:28:47Z","timestamp":1746934127000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-97674-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,6]]},"references-count":36,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["97674"],"URL":"https:\/\/doi.org\/10.1038\/s41598-025-97674-0","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,6]]},"assertion":[{"value":"20 July 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 April 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 May 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":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"15835"}}