{"id":"https://openalex.org/W4390992037","doi":"https://doi.org/10.1109/bibm58861.2023.10385444","title":"SDATNet: Self-Distillation Adversarial Training Network for AD classification","display_name":"SDATNet: Self-Distillation Adversarial Training Network for AD classification","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390992037","doi":"https://doi.org/10.1109/bibm58861.2023.10385444"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-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/A5111323306","display_name":"Tianyuan Song","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianyuan Song","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications,Beijing,China","Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023183004","display_name":"Gongpeng Cao","orcid":"https://orcid.org/0000-0002-6324-9503"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gongpeng Cao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications,Beijing,China","Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100752673","display_name":"Xiong Xiong","orcid":"https://orcid.org/0000-0001-5873-7425"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiong Xiong","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications,Beijing,China","Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085386009","display_name":"Guixia Kang","orcid":"https://orcid.org/0000-0002-4039-4505"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guixia Kang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications,Beijing,China","Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5111323306"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.3497,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67848068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2671","last_page":"2678"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8724589347839355},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7234102487564087},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7107529640197754},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.65064936876297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5608845949172974},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4229898750782013},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.0885327160358429},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.04822221398353577}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8724589347839355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7234102487564087},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7107529640197754},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.65064936876297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5608845949172974},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4229898750782013},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0885327160358429},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.04822221398353577},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7200000286102295}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1673923490","https://openalex.org/W1821462560","https://openalex.org/W1974300727","https://openalex.org/W2076622031","https://openalex.org/W2095647323","https://openalex.org/W2098505831","https://openalex.org/W2155513557","https://openalex.org/W2565639579","https://openalex.org/W2580596898","https://openalex.org/W2765366332","https://openalex.org/W2774698027","https://openalex.org/W2890950418","https://openalex.org/W2893791471","https://openalex.org/W2894357926","https://openalex.org/W2905035821","https://openalex.org/W2912541111","https://openalex.org/W2942882625","https://openalex.org/W2960357609","https://openalex.org/W2962858109","https://openalex.org/W2963557007","https://openalex.org/W2966796096","https://openalex.org/W2977883299","https://openalex.org/W2987861506","https://openalex.org/W3034200289","https://openalex.org/W3100125480","https://openalex.org/W3108850228","https://openalex.org/W3185613252","https://openalex.org/W4200633541","https://openalex.org/W4224994441","https://openalex.org/W4283029781","https://openalex.org/W4293846201","https://openalex.org/W4295095912","https://openalex.org/W4295925510","https://openalex.org/W4308610041","https://openalex.org/W4312749457","https://openalex.org/W4313182973","https://openalex.org/W4322096753","https://openalex.org/W4385245566","https://openalex.org/W6637162671","https://openalex.org/W6638523607","https://openalex.org/W6739868092","https://openalex.org/W6739901393","https://openalex.org/W6747241841","https://openalex.org/W6846418509","https://openalex.org/W6903606546"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Alzheimer\u2019s":[0],"disease":[1,46],"(AD)":[2],"is":[3,83],"a":[4,13,183],"neurodegenerative":[5],"brain":[6,51],"disorder":[7],"of":[8,19,44,72,78,125,133,143,153,162,211,239,243,257],"unknown":[9],"etiology":[10],"that":[11,31,226],"has":[12,59,92,98],"significant":[14],"impact":[15],"on":[16,47,90,194,221,232],"the":[17,42,45,76,118,131,137,141,151,160,170,209,222,253,258],"lives":[18],"patients":[20],"and":[21,38,103,122,159,179,214,241,248,255],"their":[22],"families.":[23],"Currently,":[24],"there":[25],"are":[26],"no":[27],"drugs":[28],"or":[29],"treatments":[30],"can":[32,40],"cure":[33],"AD,":[34],"but":[35,140],"early":[36],"diagnosis":[37,66,87],"intervention":[39],"mitigate":[41],"effects":[43],"patients.":[48],"Of":[49],"various":[50],"imaging":[52,57,70],"tools,":[53],"structural":[54],"magnetic":[55],"resonance":[56],"(sMRI)":[58],"been":[60],"most":[61],"intensively":[62],"studied":[63],"for":[64,107],"AD":[65,108],"as":[67],"it":[68],"provides":[69],"biomarkers":[71],"neuronal":[73],"loss.":[74],"However,":[75,111],"accuracy":[77,238],"visual":[79],"inspection":[80],"by":[81],"doctors":[82],"limited.":[84],"Therefore,":[85],"computer-aided":[86],"(CAD)":[88],"based":[89],"sMRI":[91],"important":[93],"clinical":[94],"significance.":[95],"Previous":[96],"research":[97],"employed":[99],"traditional":[100],"machine":[101],"learning":[102,105],"deep":[104],"methods":[106,113,190,231],"image":[109],"classification.":[110],"these":[112],"face":[114],"challenges":[115],"due":[116],"to":[117,191],"scarcity,":[119],"high":[120,123,154],"noise,":[121],"redundancy":[124,155],"medical":[126,157,195],"data.":[127],"Recent":[128],"studies":[129],"demonstrate":[130],"effectiveness":[132],"self-distillation":[134,166,178],"in":[135,156,165],"enhancing":[136],"model":[138,217,228],"robustness,":[139],"lack":[142,161],"additional":[144,163,199],"knowledge":[145,164],"limits":[146],"such":[147],"improvement.":[148],"To":[149],"address":[150],"issues":[152],"data":[158],"architectures,":[167],"we":[168,203],"propose":[169],"Self-Distillation":[171],"Adversarial":[172],"Training":[173],"Network":[174],"(SDATNet),":[175],"which":[176],"integrates":[177],"adversarial":[180,188],"training":[181,189],"into":[182],"single":[184],"framework.":[185],"We":[186],"utilize":[187],"simulate":[192],"noise":[193],"images,":[196],"thereby":[197],"supplementing":[198],"information.":[200],"Through":[201],"self-distillation,":[202],"achieve":[204],"cross-scale":[205],"information":[206],"interaction,":[207],"enabling":[208],"extraction":[210],"discriminative":[212],"features":[213],"effectively":[215],"improving":[216],"performance.":[218],"Experimental":[219],"validation":[220],"ADNI":[223],"dataset":[224],"demonstrates":[225],"our":[227],"outperforms":[229],"other":[230],"publicly":[233],"available":[234],"datasets,":[235],"achieving":[236],"an":[237],"92.77%":[240],"specificity":[242],"92.19%.":[244],"Our":[245],"ablation":[246],"experiments":[247],"visualization":[249],"results":[250],"further":[251],"validate":[252],"reliability":[254],"superiority":[256],"model.":[259]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
