{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T14:55:30Z","timestamp":1787064930843,"version":"build-2736575974"},"reference-count":93,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2025,1,4]],"date-time":"2025-01-04T00:00:00Z","timestamp":1735948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["LTGY23F020004"],"award-info":[{"award-number":["LTGY23F020004"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundations of China","doi-asserted-by":"crossref","award":["62271177"],"award-info":[{"award-number":["62271177"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Key Program of the Natural Science Foundation of Zhejiang Province","award":["LZ24F010007"],"award-info":[{"award-number":["LZ24F010007"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,2,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Alzheimer\u2019s disease is an irreversible central neurodegenerative disease, and early diagnosis of Alzheimer\u2019s disease is beneficial for its prevention and early intervention treatment. In this study, we propose a novel framework, FusionNet-ISBOA-MK-SVM, which integrates a fusion network (FusionNet) and improved secretary bird optimization algorithm to optimize multikernel support vector machine for Alzheimer\u2019s disease diagnosis. The model leverages multimodality data, including functional magnetic resonance imaging and genetic information (single-nucleotide polymorphisms). Specifically, FusionNet employs U-shaped hierarchical graph convolutional networks and sparse graph attention networks to select feature effectively. Extensive validation using the Alzheimer\u2019s Disease Neuroimaging Initiative dataset demonstrates the model\u2019s superior interpretability and classification performance. Compared to other state-of-the-art machine learning methods, FusionNet-ISBOA-MK-SVM achieves classification accuracies of 98.6%, 95.7%, 93.0%, 91.8%, 93.1%, and 95.4% for HC vs. AD, EMCI vs. AD, LMCI vs. AD, EMCI vs. AD, HC vs. EMCI, and HC vs. LMCI, respectively. Moreover, the proposed model identifies affected brain regions and pathogenic genes, offering deeper insights into the mechanisms and progression of Alzheimer\u2019s disease. These findings provide valuable scientific evidence to support early diagnosis and preventive strategies for Alzheimer\u2019s disease.<\/jats:p>","DOI":"10.1093\/cercor\/bhae498","type":"journal-article","created":{"date-parts":[[2024,12,22]],"date-time":"2024-12-22T15:22:46Z","timestamp":1734880966000},"source":"Crossref","is-referenced-by-count":4,"title":["Diagnosis of Alzheimer\u2019s disease using FusionNet with improved secretary bird optimization algorithm for optimal MK-SVM based on imaging genetic data"],"prefix":"10.1093","volume":"35","author":[{"given":"Luyun","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Hangzhou Dianzi University , 1158 2nd Street, Hangzhou, Zhejiang 310018 ,","place":["China"]},{"name":"Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health , Ministry of Industry and Information Technology of China, 215 6th Street, Hangzhou, Zhejiang 310018 ,","place":["China"]},{"name":"Hangzhou Vocational & Technical College , 68 Xueyuan Street, Hangzhou, Zhejiang 310018 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7662-9126","authenticated-orcid":false,"given":"Jinhua","family":"Sheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Hangzhou Dianzi University , 1158 2nd Street, Hangzhou, Zhejiang 310018 ,","place":["China"]},{"name":"Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health , Ministry of Industry and Information Technology of China, 215 6th Street, Hangzhou, Zhejiang 310018 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Hospital , 1 Dahua Road, Beijing 100730 ,","place":["China"]},{"name":"National Center of Gerontology , 1 Dahua Road, Beijing 100730 ,","place":["China"]},{"name":"Institute of Geriatric Medicine , Chinese Academy of Medical Sciences, 1 Dahua Road, Beijing 100730 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Song","sequence":"additional","affiliation":[{"name":"Beijing Hospital , 1 Dahua Road, Beijing 100730 ,","place":["China"]},{"name":"National Center of Gerontology , 1 Dahua Road, Beijing 100730 ,","place":["China"]},{"name":"Institute of Geriatric Medicine , Chinese Academy of Medical Sciences, 1 Dahua Road, Beijing 100730 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Hangzhou Dianzi University , 1158 2nd Street, Hangzhou, Zhejiang 310018 ,","place":["China"]},{"name":"Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China , 215 6th Street, Hangzhou, Zhejiang 310018 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Binbing","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Hangzhou Dianzi University , 1158 2nd Street, Hangzhou, Zhejiang 310018 ,","place":["China"]},{"name":"Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health , Ministry of Industry and Information Technology of China, 215 6th Street, Hangzhou, Zhejiang 310018 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Hangzhou Dianzi University , 1158 2nd Street, Hangzhou, Zhejiang 310018 ,","place":["China"]},{"name":"Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China , 215 6th Street, Hangzhou, Zhejiang 310018 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,1,4]]},"reference":[{"key":"2025021207214813600_ref1","doi-asserted-by":"crossref","first-page":"115079","DOI":"10.1016\/j.eswa.2021.115079","article-title":"RUN beyond the metaphor: an efficient optimization algorithm based on Runge Kutta method","volume":"181","author":"Ahmadianfar","year":"2021","journal-title":"Expert Syst Appl"},{"key":"2025021207214813600_ref2","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1186\/s40478-023-01563-4","article-title":"Large multi-ethnic genetic analyses of amyloid imaging identify new genes for Alzheimer disease","volume":"11","author":"Ali","year":"2023","journal-title":"Acta Neuropathol Commun"},{"key":"2025021207214813600_ref3","doi-asserted-by":"publisher","first-page":"1564","DOI":"10.1038\/nprot.2010.116","article-title":"Data quality control in genetic case-control association studies","volume":"5","author":"Anderson","year":"2010","journal-title":"Nat Protoc"},{"key":"2025021207214813600_ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3199712","article-title":"Optimization of RBF-SVM kernel using grid search algorithm for DDoS attack detection in SDN-based VANET","volume":"10","author":"Anyanwu","year":"2022","journal-title":"IEEE Internet Things J"},{"key":"2025021207214813600_ref5","doi-asserted-by":"publisher","first-page":"5690","DOI":"10.1002\/alz.13319","article-title":"A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer's disease risk and rates of disease progression","volume":"19","author":"Bae","year":"2023","journal-title":"Alzheimers Dement"},{"key":"2025021207214813600_ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s11357-024-01128-w","article-title":"Age-related changes in human brain functional connectivity using graph theory and machine learning techniques in resting-state fMRI data","volume":"46","author":"Baghernezhad","year":"2024","journal-title":"GeroScience"},{"key":"2025021207214813600_ref7","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/s11357-017-9977-7","article-title":"Loss of gait control assessed by cognitive-motor dual-tasks: pros and cons in detecting people at risk of developing Alzheimer\u2019s and Parkinson\u2019s diseases","volume":"39","author":"Belghali","year":"2017","journal-title":"Geroscience"},{"key":"2025021207214813600_ref8","doi-asserted-by":"publisher","first-page":"1366","DOI":"10.1038\/s41593-022-01166-7","article-title":"The three-dimensional landscape of cortical chromatin accessibility in Alzheimer\u2019s disease","volume":"25","author":"Bendl","year":"2022","journal-title":"Nat Neurosci"},{"key":"2025021207214813600_ref9","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1038\/sj.mp.4002089","article-title":"Evidence for induction of the ornithine transcarbamylase expression in Alzheimer's disease","volume":"14","author":"Bensemain","year":"2009","journal-title":"Mol Psychiatry"},{"key":"2025021207214813600_ref10","doi-asserted-by":"crossref","first-page":"8342104","DOI":"10.1155\/2023\/8342104","article-title":"Deep learning with graph convolutional networks: an overview and latest applications in computational intelligence","volume":"2023","author":"Bhatti","year":"2023","journal-title":"Int J Intell Syst"},{"key":"2025021207214813600_ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3212700","article-title":"Hypergraph structural information aggregation generative adversarial networks for diagnosis and pathogenetic factors identification of Alzheimer\u2019s disease with imaging genetic data","volume":"35","author":"Bi","year":"2022","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"2025021207214813600_ref12","doi-asserted-by":"publisher","first-page":"bbac137","DOI":"10.1093\/bib\/bbac137","article-title":"Feature aggregation graph convolutional network based on imaging genetic data for diagnosis and pathogeny identification of Alzheimer\u2019s disease","volume":"23","author":"Bi","year":"2022","journal-title":"Brief Bioinform"},{"key":"2025021207214813600_ref13","doi-asserted-by":"publisher","first-page":"101950","DOI":"10.1016\/j.inffus.2023.101950","article-title":"Explainable and programmable hypergraph convolutional network for imaging genetics data fusion","volume":"100","author":"Bi","year":"2023","journal-title":"Inf Fusion"},{"key":"2025021207214813600_ref14","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.neucom.2019.10.118","article-title":"A comprehensive survey on support vector machine classification: applications, challenges and trends","volume":"408","author":"Cervantes","year":"2020","journal-title":"Neurocomputing"},{"key":"2025021207214813600_ref15","doi-asserted-by":"publisher","first-page":"107866","DOI":"10.1016\/j.asoc.2021.107866","article-title":"SHADE\u2013WOA: a metaheuristic algorithm for global optimization","volume":"113","author":"Chakraborty","year":"2021","journal-title":"Appl Soft Comput"},{"key":"2025021207214813600_ref16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1961189.1961199","article-title":"LIBSVM: a library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM transactions on intelligent systems and technology (TIST)"},{"key":"2025021207214813600_ref17","doi-asserted-by":"publisher","first-page":"1158","DOI":"10.3390\/biom10081158","article-title":"Cellular mechanisms of melatonin: insight from neurodegenerative diseases","volume":"10","author":"Chen","year":"2020","journal-title":"Biomol Ther"},{"key":"2025021207214813600_ref18","doi-asserted-by":"publisher","first-page":"1604","DOI":"10.3390\/ijms23031604","article-title":"Alzheimer\u2019s disease-associated SNP rs708727 in SLC41A1 may increase risk for Parkinson\u2019s disease: report from enlarged Slovak study","volume":"23","author":"Cibulka","year":"2022","journal-title":"Int J Mol Sci"},{"key":"2025021207214813600_ref19","doi-asserted-by":"publisher","first-page":"4765","DOI":"10.1007\/s10462-022-10275-5","article-title":"Recent advances in decision trees: an updated survey","volume":"56","author":"Costa","year":"2023","journal-title":"Artif Intell Rev"},{"key":"2025021207214813600_ref20","doi-asserted-by":"publisher","first-page":"104316","DOI":"10.1016\/j.chemolab.2021.104316","article-title":"Adaptive LASSO logistic regression based on particle swarm optimization for Alzheimer's disease early diagnosis","volume":"215","author":"Cui","year":"2021","journal-title":"Chemom Intell Lab Syst"},{"key":"2025021207214813600_ref21","doi-asserted-by":"publisher","first-page":"1136","DOI":"10.3390\/math11051136","article-title":"Hybrid whale and Gray wolf deep learning optimization algorithm for prediction of Alzheimer\u2019s disease","volume":"11","author":"Dhakhinamoorthy","year":"2023","journal-title":"Mathematics"},{"key":"2025021207214813600_ref22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10462-024-10729-y","article-title":"Secretary bird optimization algorithm: a new metaheuristic for solving global optimization problems","volume":"57","author":"Fu","year":"2024","journal-title":"Artif Intell Rev"},{"key":"2025021207214813600_ref23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10462-024-10716-3","article-title":"Red-billed blue magpie optimizer: a novel metaheuristic algorithm for 2D\/3D UAV path planning and engineering design problems","volume":"57","author":"Fu","year":"2024","journal-title":"Artif Intell Rev"},{"key":"2025021207214813600_ref24","doi-asserted-by":"publisher","first-page":"1175","DOI":"10.1038\/nn.4361","article-title":"The human connectome project's neuroimaging approach","volume":"19","author":"Glasser","year":"2016","journal-title":"Nat Neurosci"},{"key":"2025021207214813600_ref25","doi-asserted-by":"publisher","first-page":"100310","DOI":"10.1016\/j.health.2024.100310","article-title":"A novel deep learning graph attention network for Alzheimer\u2019s disease image segmentation","volume":"5","author":"Hasan","year":"2024","journal-title":"Healthc Anal"},{"key":"2025021207214813600_ref26","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1038\/s41592-024-02237-2","article-title":"Brainlife. Io: a decentralized and open-source cloud platform to support neuroscience research","volume":"21","author":"Hayashi","year":"2024","journal-title":"Nat Methods"},{"key":"2025021207214813600_ref27","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","article-title":"Harris hawks optimization: algorithm and applications","volume":"97","author":"Heidari","year":"2019","journal-title":"Futur Gener Comput Syst"},{"key":"2025021207214813600_ref28","doi-asserted-by":"publisher","first-page":"101979","DOI":"10.1016\/j.aei.2023.101979","article-title":"Intelligent fault diagnosis of turbine blade cracks via multiscale sparse filtering and multi-kernel support vector machine for information fusion","volume":"56","author":"Huang","year":"2023","journal-title":"Adv Eng Inform"},{"key":"2025021207214813600_ref29","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.tins.2022.11.006","article-title":"Entorhinal cortex dysfunction in Alzheimer's disease","volume":"46","author":"Igarashi","year":"2023","journal-title":"Trends Neurosci"},{"key":"2025021207214813600_ref30","doi-asserted-by":"publisher","DOI":"10.3233\/jad-230689","article-title":"GRN missense variants and familial Alzheimer\u2019s disease: two case reports","volume":"96","author":"Ingannato","year":"2023","journal-title":"J Alzheimers Dis"},{"key":"2025021207214813600_ref31","doi-asserted-by":"publisher","first-page":"821","DOI":"10.1007\/s00401-022-02454-z","article-title":"Genome-wide meta-analysis for Alzheimer\u2019s disease cerebrospinal fluid biomarkers","volume":"144","author":"Jansen","year":"2022","journal-title":"Acta Neuropathol"},{"key":"2025021207214813600_ref32","doi-asserted-by":"publisher","first-page":"1919","DOI":"10.1007\/s10462-023-10567-4","article-title":"Crayfish optimization algorithm","volume":"56","author":"Jia","year":"2023","journal-title":"Artif Intell Rev"},{"key":"2025021207214813600_ref33","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1186\/s13024-023-00633-4","article-title":"A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores","volume":"18","author":"Kang","year":"2023","journal-title":"Mol Neurodegener"},{"key":"2025021207214813600_ref34","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.isprsjprs.2020.12.010","article-title":"Review on convolutional neural networks (CNN) in vegetation remote sensing","volume":"173","author":"Kattenborn","year":"2021","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"2025021207214813600_ref35","doi-asserted-by":"publisher","first-page":"123076","DOI":"10.1016\/j.molliq.2023.123076","article-title":"Experimental and computational investigation of the binding mechanism of thymol with human transferrin: importance of dietary phytochemicals in Alzheimer\u2019s disease therapeutics","volume":"390","author":"Khan","year":"2023","journal-title":"J Mol Liq"},{"key":"2025021207214813600_ref36","doi-asserted-by":"publisher","first-page":"1529","DOI":"10.3390\/math11061529","article-title":"Genetics information with functional brain networks for dementia classification","volume":"11","author":"Khatri","year":"2023","journal-title":"Mathematics"},{"key":"2025021207214813600_ref37","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1016\/j.neunet.2021.08.030","article-title":"Working memory connections for LSTM","volume":"144","author":"Landi","year":"2021","journal-title":"Neural Netw"},{"key":"2025021207214813600_ref38","doi-asserted-by":"publisher","first-page":"112994","DOI":"10.1016\/j.celrep.2023.112994","article-title":"Cell-type-specific regulation of APOE and CLU levels in human neurons by the Alzheimer\u2019s disease risk gene SORL1","volume":"42","author":"Lee","year":"2023","journal-title":"Cell Rep"},{"key":"2025021207214813600_ref39","doi-asserted-by":"publisher","first-page":"103213","DOI":"10.1016\/j.media.2024.103213","article-title":"Alzheimer\u2019s disease diagnosis from multi-modal data via feature inductive learning and dual multilevel graph neural network","volume":"97","author":"Lei","year":"2024","journal-title":"Med Image Anal"},{"key":"2025021207214813600_ref40","doi-asserted-by":"publisher","first-page":"123826","DOI":"10.1016\/j.apenergy.2024.123826","article-title":"Advancing fractured geothermal system modeling with artificial neural network and bidirectional gated recurrent unit","volume":"372","author":"Li","year":"2024","journal-title":"Appl Energy"},{"key":"2025021207214813600_ref41","doi-asserted-by":"publisher","first-page":"129604","DOI":"10.1016\/j.energy.2023.129604","article-title":"A dual-optimization wind speed forecasting model based on deep learning and improved dung beetle optimization algorithm","volume":"286","author":"Li","year":"2024","journal-title":"Energy"},{"key":"2025021207214813600_ref42","doi-asserted-by":"publisher","first-page":"e33","DOI":"10.1016\/j.jinf.2020.06.072","article-title":"Elevation of ACE2 as a SARS-CoV-2 entry receptor gene expression in Alzheimer's disease","volume":"81","author":"Lim","year":"2020","journal-title":"J Infect"},{"key":"2025021207214813600_ref43","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-01587-8","volume-title":"Introduction to graph neural networks","author":"Liu","year":"2020"},{"key":"2025021207214813600_ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3360429","article-title":"Federated graph neural networks: overview, techniques, and challenges","volume":"2","author":"Liu","year":"2024","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"2025021207214813600_ref45","doi-asserted-by":"publisher","first-page":"119951","DOI":"10.1016\/j.ins.2023.119951","article-title":"TRNN: an efficient time-series recurrent neural network for stock price prediction","volume":"657","author":"Lu","year":"2024","journal-title":"Inf Sci"},{"key":"2025021207214813600_ref46","doi-asserted-by":"publisher","first-page":"106930","DOI":"10.1016\/j.compbiomed.2023.106930","article-title":"Effective detection of Alzheimer's disease by optimizing fuzzy K-nearest neighbors based on salp swarm algorithm","volume":"159","author":"Lu","year":"2023","journal-title":"Comput Biol Med"},{"key":"2025021207214813600_ref47","doi-asserted-by":"publisher","first-page":"107000","DOI":"10.1016\/j.patcog.2019.107000","article-title":"Dynamic graph convolutional networks","volume":"97","author":"Manessi","year":"2020","journal-title":"Pattern Recogn"},{"key":"2025021207214813600_ref48","doi-asserted-by":"publisher","first-page":"101133","DOI":"10.1016\/j.arr.2020.101133","article-title":"Risk for Alzheimer\u2019s disease: a review of long-term episodic memory encoding and retrieval fMRI studies","volume":"62","author":"McDonough","year":"2020","journal-title":"Ageing Res Rev"},{"key":"2025021207214813600_ref49","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.ins.2021.11.076","article-title":"PSO-sono: a novel PSO variant for single-objective numerical optimization","volume":"586","author":"Meng","year":"2022","journal-title":"Inf Sci"},{"key":"2025021207214813600_ref50","doi-asserted-by":"publisher","first-page":"837","DOI":"10.3390\/genes13050837","article-title":"Feature fusion and detection in Alzheimer\u2019s disease using a novel genetic multi-kernel SVM based on MRI imaging and gene data","volume":"13","author":"Meng","year":"2022","journal-title":"Genes"},{"key":"2025021207214813600_ref51","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s00018-023-04791-y","article-title":"Proteomics analysis of prefrontal cortex of Alzheimer\u2019s disease patients revealed dysregulated proteins in the disease and novel proteins associated with amyloid-\u03b2 pathology","volume":"80","author":"Montero-Calle","year":"2023","journal-title":"Cell Mol Life Sci"},{"key":"2025021207214813600_ref52","doi-asserted-by":"publisher","first-page":"1057","DOI":"10.2174\/1871527321666220614110616","article-title":"A concise review of common plant-derived compounds as a potential therapy for Alzheimer's disease and Parkinson's disease: insight into structure-activity-relationship","volume":"22","author":"Nishal","year":"2023","journal-title":"CNS Neurol Disord Drug Targets"},{"key":"2025021207214813600_ref53","doi-asserted-by":"publisher","first-page":"122189","DOI":"10.1016\/j.eswa.2023.122189","article-title":"An improved sand cat swarm optimization for moving target search by UAV","volume":"238","author":"Niu","year":"2024","journal-title":"Expert Syst Appl"},{"key":"2025021207214813600_ref54","doi-asserted-by":"publisher","first-page":"e0259677","DOI":"10.1371\/journal.pone.0259677","article-title":"MEG activity of the dorsolateral prefrontal cortex during optic flow stimulations detects mild cognitive impairment due to Alzheimer\u2019s disease","volume":"16","author":"Noguchi-Shinohara","year":"2021","journal-title":"PLoS One"},{"key":"2025021207214813600_ref55","doi-asserted-by":"publisher","first-page":"296","DOI":"10.1038\/s41398-021-01412-9","article-title":"Novel Alzheimer\u2019s disease risk variants identified based on whole-genome sequencing of APOE \u03b54 carriers","volume":"11","author":"Park","year":"2021","journal-title":"Transl Psychiatry"},{"key":"2025021207214813600_ref56","doi-asserted-by":"publisher","first-page":"7218","DOI":"10.1523\/JNEUROSCI.2574-18.2019","article-title":"Neuroinflammation and functional connectivity in Alzheimer's disease: interactive influences on cognitive performance","volume":"39","author":"Passamonti","year":"2019","journal-title":"J Neurosci"},{"key":"2025021207214813600_ref57","doi-asserted-by":"publisher","first-page":"1941","DOI":"10.1109\/TAFFC.2022.3189222","article-title":"Joint feature adaptation and graph adaptive label propagation for cross-subject emotion recognition from EEG signals","volume":"13","author":"Peng","year":"2022","journal-title":"IEEE Trans Affect Comput"},{"key":"2025021207214813600_ref58","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1086\/519795","article-title":"PLINK: a tool set for whole-genome association and population-based linkage analyses","volume":"81","author":"Purcell","year":"2007","journal-title":"Am J Hum Genet"},{"key":"2025021207214813600_ref60","volume-title":"2020 IEEE Congress on Evolutionary Computation (CEC)","author":"Salgotra","year":"2020"},{"key":"2025021207214813600_ref61","doi-asserted-by":"publisher","first-page":"2627","DOI":"10.1007\/s00366-022-01604-x","article-title":"Sand cat swarm optimization: a nature-inspired algorithm to solve global optimization problems","volume":"39","author":"Seyyedabbasi","year":"2023","journal-title":"Eng Comput"},{"key":"2025021207214813600_ref62","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1016\/j.bbr.2019.03.004","article-title":"A novel joint HCPMMP method for automatically classifying Alzheimer\u2019s and different stage MCI patients","volume":"365","author":"Sheng","year":"2019","journal-title":"Behav Brain Res"},{"key":"2025021207214813600_ref63","doi-asserted-by":"publisher","first-page":"5475","DOI":"10.1038\/s41598-020-62378-0","article-title":"Alzheimer\u2019s disease, mild cognitive impairment, and normal aging distinguished by multi-modal parcellation and machine learning","volume":"10","author":"Sheng","year":"2020","journal-title":"Sci Rep"},{"key":"2025021207214813600_ref64","doi-asserted-by":"publisher","first-page":"2405","DOI":"10.1038\/s41598-022-06444-9","article-title":"Predictive classification of Alzheimer\u2019s disease using brain imaging and genetic data","volume":"12","author":"Sheng","year":"2022","journal-title":"Sci Rep"},{"key":"2025021207214813600_ref65","doi-asserted-by":"publisher","first-page":"108035","DOI":"10.1016\/j.compbiomed.2024.108035","article-title":"A hybrid multimodal machine learning model for detecting Alzheimer's disease","volume":"170","author":"Sheng","year":"2024","journal-title":"Comput Biol Med"},{"key":"2025021207214813600_ref66","doi-asserted-by":"publisher","first-page":"132306","DOI":"10.1016\/j.physd.2019.132306","article-title":"Fundamentals of recurrent neural network (RNN) and long short-term memory (LSTM) network","volume":"404","author":"Sherstinsky","year":"2020","journal-title":"Phys D Nonlinear Phenom"},{"key":"2025021207214813600_ref67","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1038\/s41398-021-01272-3","article-title":"Ethnic and trans-ethnic genome-wide association studies identify new loci influencing Japanese Alzheimer\u2019s disease risk","volume":"11","author":"Shigemizu","year":"2021","journal-title":"Transl Psychiatry"},{"key":"2025021207214813600_ref68","doi-asserted-by":"publisher","first-page":"149","DOI":"10.3390\/biomimetics8020149","article-title":"Subtraction-average-based optimizer: a new swarm-inspired metaheuristic algorithm for solving optimization problems","volume":"8","author":"Trojovsk\u00fd","year":"2023","journal-title":"Biomimetics"},{"key":"2025021207214813600_ref69","volume-title":"Future Internet"},{"key":"2025021207214813600_ref70","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1186\/s12974-023-02850-6","article-title":"Alzheimer\u2019s disease-associated complement gene variants influence plasma complement protein levels","volume":"20","author":"Veteleanu","year":"2023","journal-title":"J Neuroinflammation"},{"key":"2025021207214813600_ref71","doi-asserted-by":"publisher","first-page":"116578","DOI":"10.1016\/j.cma.2023.116578","article-title":"An extreme learning machine-based method for computational PDEs in higher dimensions","volume":"418","author":"Wang","year":"2024","journal-title":"Comput Methods Appl Mech Eng"},{"key":"2025021207214813600_ref72","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1016\/j.gpb.2021.08.005","article-title":"GAPIT version 3: boosting power and accuracy for genomic association and prediction","volume":"19","author":"Wang","year":"2021","journal-title":"Genomics Proteomics Bioinformatics"},{"key":"2025021207214813600_ref73","doi-asserted-by":"publisher","first-page":"118001","DOI":"10.1016\/j.neuroimage.2021.118001","article-title":"U-net model for brain extraction: trained on humans for transfer to non-human primates","volume":"235","author":"Wang","year":"2021","journal-title":"NeuroImage"},{"key":"2025021207214813600_ref74","doi-asserted-by":"publisher","first-page":"bhae329","DOI":"10.1093\/cercor\/bhae329","article-title":"A novel sand cat swarm optimization algorithm-based SVM for diagnosis imaging genomics in Alzheimer\u2019s disease","volume":"34","author":"Wang","year":"2024","journal-title":"Cereb Cortex"},{"key":"2025021207214813600_ref75","doi-asserted-by":"publisher","first-page":"994","DOI":"10.1038\/ng.3052","article-title":"Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer","volume":"46","author":"Wolpin","year":"2014","journal-title":"Nat Genet"},{"key":"2025021207214813600_ref76","doi-asserted-by":"publisher","first-page":"2838","DOI":"10.1007\/s12035-018-1242-2","article-title":"DAPK1: a novel pathology and treatment target for Alzheimer\u2019s disease","volume":"56","author":"Xu","year":"2019","journal-title":"Mol Neurobiol"},{"key":"2025021207214813600_ref77","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1080\/21642583.2019.1708830","article-title":"A novel swarm intelligence optimization approach: sparrow search algorithm","volume":"8","author":"Xue","year":"2020","journal-title":"Syst Sci Control Eng"},{"key":"2025021207214813600_ref78","doi-asserted-by":"publisher","first-page":"7305","DOI":"10.1007\/s11227-022-04959-6","article-title":"Dung beetle optimizer: a new meta-heuristic algorithm for global optimization","volume":"79","author":"Xue","year":"2023","journal-title":"J Supercomput"},{"key":"2025021207214813600_ref79","doi-asserted-by":"publisher","first-page":"1048","DOI":"10.1016\/j.neuron.2020.09.005","article-title":"Artificial neural networks for neuroscientists: a primer","volume":"107","author":"Yang","year":"2020","journal-title":"Neuron"},{"key":"2025021207214813600_ref80","doi-asserted-by":"publisher","first-page":"bhad477","DOI":"10.1093\/cercor\/bhad477","article-title":"Towards an accurate autism spectrum disorder diagnosis: multiple connectome views from fMRI data","volume":"34","author":"Yang","year":"2024","journal-title":"Cereb Cortex"},{"key":"2025021207214813600_ref81","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TKDE.2021.3072345","article-title":"Sparse graph attention networks","volume":"35","author":"Ye","year":"2021","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2025021207214813600_ref82","doi-asserted-by":"publisher","first-page":"e082910","DOI":"10.1002\/alz.082910","article-title":"Tau pathway-based gene analysis in the Alzheimer\u2019s disease continuum identifies CLU and FYN associated with tau deposition on PET in a Korean cohort","volume":"19","author":"Yi","year":"2023","journal-title":"Alzheimers Dement"},{"key":"2025021207214813600_ref83","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.neucom.2018.09.001","article-title":"A new switching-delayed-PSO-based optimized SVM algorithm for diagnosis of Alzheimer\u2019s disease","volume":"320","author":"Zeng","year":"2018","journal-title":"Neurocomputing"},{"key":"2025021207214813600_ref84","doi-asserted-by":"publisher","first-page":"4663","DOI":"10.1109\/TKDE.2021.3049250","article-title":"Challenges in KNN classification","volume":"34","author":"Zhang","year":"2021","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2025021207214813600_ref85","doi-asserted-by":"publisher","first-page":"429","DOI":"10.3389\/fnagi.2021.688926","article-title":"Predicting MCI to AD conversation using integrated sMRI and rs-fMRI: machine learning and graph theory approach","volume":"13","author":"Zhang","year":"2021","journal-title":"Front Aging Neurosci"},{"key":"2025021207214813600_ref86","doi-asserted-by":"publisher","first-page":"107392","DOI":"10.1016\/j.compbiomed.2023.107392","article-title":"Enhanced Harris hawks optimization-based fuzzy k-nearest neighbor algorithm for diagnosis of Alzheimer's disease","volume":"165","author":"Zhang","year":"2023","journal-title":"Comput Biol Med"},{"key":"2025021207214813600_ref87","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1007\/s11357-023-00897-0","article-title":"Glucose metabolism in posterior cingulate cortex has supplementary value to predict the progression of cognitively unimpaired to dementia due to Alzheimer\u2019s disease: an exploratory study of 18F-FDG-PET","volume":"46","author":"Zhang","year":"2024","journal-title":"Geroscience"},{"key":"2025021207214813600_ref88","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1186\/s40035-023-00395-5","article-title":"Death-associated protein kinase 1 as a therapeutic target for Alzheimer's disease","volume":"13","author":"Zhang","year":"2024","journal-title":"Transl Neurodegener"},{"key":"2025021207214813600_ref89","doi-asserted-by":"publisher","first-page":"7204","DOI":"10.1002\/int.22586","article-title":"MR-DCAE: manifold regularization-based deep convolutional autoencoder for unauthorized broadcasting identification","volume":"36","author":"Zheng","year":"2021","journal-title":"Int J Intell Syst"},{"key":"2025021207214813600_ref90","doi-asserted-by":"publisher","first-page":"1298","DOI":"10.1109\/LCOMM.2022.3145647","article-title":"Fine-grained modulation classification using multi-scale radio transformer with dual-channel representation","volume":"26","author":"Zheng","year":"2022","journal-title":"IEEE Commun Lett"},{"key":"2025021207214813600_ref91","doi-asserted-by":"publisher","first-page":"596","DOI":"10.3390\/drones7100596","article-title":"MobileRaT: a lightweight radio transformer method for automatic modulation classification in drone communication systems","volume":"7","author":"Zheng","year":"2023","journal-title":"Drones"},{"key":"2025021207214813600_ref92","doi-asserted-by":"publisher","first-page":"109241","DOI":"10.1016\/j.epsr.2023.109241","article-title":"A real-time transformer discharge pattern recognition method based on CNN-LSTM driven by few-shot learning","volume":"219","author":"Zheng","year":"2023","journal-title":"Electr Power Syst Res"},{"key":"2025021207214813600_ref93","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1007\/s11571-023-10015-7","article-title":"A real-time constellation image classification method of wireless communication signals based on the lightweight network MobileViT","volume":"18","author":"Zheng","year":"2024","journal-title":"Cogn Neurodyn"},{"key":"2025021207214813600_ref94","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.inffus.2021.07.013","article-title":"Interpretable learning based dynamic graph convolutional networks for alzheimer\u2019s disease analysis","volume":"77","author":"Zhu","year":"2022","journal-title":"Inf Fusion"}],"container-title":["Cerebral Cortex"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/cercor\/article-pdf\/35\/2\/bhae498\/61329356\/bhae498.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/cercor\/article-pdf\/35\/2\/bhae498\/61329356\/bhae498.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,12]],"date-time":"2025-02-12T02:22:09Z","timestamp":1739326929000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/cercor\/article\/doi\/10.1093\/cercor\/bhae498\/7942657"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,4]]},"references-count":93,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,2,5]]}},"URL":"https:\/\/doi.org\/10.1093\/cercor\/bhae498","relation":{},"ISSN":["1047-3211","1460-2199"],"issn-type":[{"value":"1047-3211","type":"print"},{"value":"1460-2199","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,2]]},"published":{"date-parts":[[2025,1,4]]},"article-number":"bhae498"}}