{"id":"https://openalex.org/W4415178743","doi":"https://doi.org/10.1109/lsp.2025.3621339","title":"MADF-Net: A Multi-Branch Adaptive Deep Fusion Network for Alzheimer's Disease Prediction","display_name":"MADF-Net: A Multi-Branch Adaptive Deep Fusion Network for Alzheimer's Disease Prediction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415178743","doi":"https://doi.org/10.1109/lsp.2025.3621339"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2025.3621339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3621339","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100742126","display_name":"Ning Wang","orcid":"https://orcid.org/0000-0003-3546-0966"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Wang","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"],"raw_orcid":"https://orcid.org/0000-0003-3546-0966","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Pingan Tian","orcid":"https://orcid.org/0009-0009-0415-7199"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pingan Tian","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"],"raw_orcid":"https://orcid.org/0009-0009-0415-7199","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111938904","display_name":"Meng-Jhen Wu","orcid":"https://orcid.org/0009-0001-8434-4307"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghui Wu","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100570342","display_name":"Haojie Zhou","orcid":"https://orcid.org/0009-0009-1686-3410"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojie Zhou","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"],"raw_orcid":"https://orcid.org/0009-0009-1686-3410","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I111599522"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2876975,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":null,"first_page":"4204","last_page":"4208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9487000107765198,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9487000107765198,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9039000272750854,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7294999957084656},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.6804999709129333},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.6280999779701233},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5913000106811523},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5271000266075134},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4875999987125397},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4537000060081482},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.43709999322891235}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7294999957084656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7110999822616577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7020999789237976},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.6804999709129333},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6280999779701233},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5913000106811523},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5271000266075134},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4945000112056732},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4875999987125397},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4537000060081482},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.43709999322891235},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41999998688697815},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3625999987125397},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3596000075340271},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2992999851703644},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.29350000619888306},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28349998593330383},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.2648000121116638}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2025.3621339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3621339","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3480854787","display_name":null,"funder_award_id":"JUSRP123035","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1853705225","https://openalex.org/W1983850663","https://openalex.org/W2074037951","https://openalex.org/W2116709840","https://openalex.org/W2129497119","https://openalex.org/W2159122349","https://openalex.org/W2798054687","https://openalex.org/W2809150600","https://openalex.org/W2896457183","https://openalex.org/W2903517662","https://openalex.org/W3014251530","https://openalex.org/W3096609969","https://openalex.org/W3125401821","https://openalex.org/W3134253398","https://openalex.org/W3159530258","https://openalex.org/W3196716035","https://openalex.org/W3198901578","https://openalex.org/W3209059054","https://openalex.org/W4206413203","https://openalex.org/W4211264657","https://openalex.org/W4213174719","https://openalex.org/W4224068866","https://openalex.org/W4289517144","https://openalex.org/W4311059915","https://openalex.org/W4313070576","https://openalex.org/W4320896605","https://openalex.org/W4386639948","https://openalex.org/W4399714298","https://openalex.org/W4405269847"],"related_works":[],"abstract_inverted_index":{"Alzheimer's":[0],"disease":[1],"(AD)":[2],"is":[3,100,132],"one":[4],"of":[5,14,23,30,48,67,73,108,119,171,177],"the":[6,12,15,21,35,43,65,77,83,90,106,116,120,130,137,144,151],"key":[7],"diseases":[8],"that":[9,160],"seriously":[10],"threatens":[11],"health":[13],"elderly":[16,25],"population":[17],"and":[18,46,89,104,142,173],"significantly":[19],"increases":[20],"burden":[22],"social":[24],"care.":[26],"The":[27,70,98,111],"widespread":[28],"application":[29],"artificial":[31],"intelligence":[32],"technology":[33],"in":[34],"medical":[36],"field":[37],"has":[38],"brought":[39],"new":[40],"ideas":[41],"for":[42],"early":[44],"diagnosis":[45],"intervention":[47],"AD.":[49],"To":[50],"this":[51],"end,":[52],"we":[53],"propose":[54],"a":[55],"novel":[56],"Multi-Branch":[57,84],"Adaptive":[58,85],"Deep":[59,93],"Fusion":[60,86,94],"Network":[61],"(MADF-Net)":[62],"to":[63,102,114,134],"improve":[64],"accuracy":[66,170],"AD":[68],"diagnosis.":[69],"MADF-Net":[71,163],"consists":[72],"three":[74],"main":[75,117],"parts:":[76],"Supervised":[78],"Autoencoder":[79],"Alignment":[80],"Module":[81,87,96],"(S-AEAM),":[82],"(MAFusion),":[88],"Dynamic":[91],"Gated":[92],"Decision":[95],"(DGD-Fusion).":[97],"S-AEAM":[99],"used":[101],"align":[103],"enhance":[105],"features":[107,125,138],"different":[109],"modalities.":[110,128],"MAFusion":[112],"aims":[113],"retain":[115],"information":[118],"current":[121],"modality":[122],"while":[123],"integrating":[124],"from":[126,139,157],"other":[127],"Finally,":[129],"DGD-Fusion":[131],"employed":[133],"deeply":[135],"fuse":[136],"all":[140],"modalities":[141],"obtain":[143],"final":[145],"output.":[146],"Extensive":[147],"experiments":[148],"conducted":[149],"on":[150],"<italic":[152],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[153],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Cookie":[154],"Theft</i>":[155],"corpus":[156],"DementiaBank":[158],"demonstrate":[159],"our":[161],"proposed":[162],"outperforms":[164],"state-of-the-art":[165],"(SOTA)":[166],"models,":[167],"achieving":[168],"an":[169,174],"88.91%":[172],"F1":[175],"score":[176],"90.48%.":[178]},"counts_by_year":[],"updated_date":"2025-11-11T23:18:09.558992","created_date":"2025-10-15T00:00:00"}