{"id":"https://openalex.org/W7126043784","doi":"https://doi.org/10.1109/bibm66473.2025.11356237","title":"R-SSAE: Riemannian Manifold Sparse Siamese Autoencoder for Autism Spectrum Disorder Diagnosis via Functional Connectivity","display_name":"R-SSAE: Riemannian Manifold Sparse Siamese Autoencoder for Autism Spectrum Disorder Diagnosis via Functional Connectivity","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126043784","doi":"https://doi.org/10.1109/bibm66473.2025.11356237"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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":null,"display_name":"Yuanyuan Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuanyuan Zheng","raw_affiliation_strings":["College of Computer and Information Science, Chongqing Normal University,China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Chongqing Normal University,China","institution_ids":["https://openalex.org/I126924076"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124059383","display_name":"Zeming Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeming Chen","raw_affiliation_strings":["College of Computer and Information Science, Chongqing Normal University,China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Chongqing Normal University,China","institution_ids":["https://openalex.org/I126924076"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124068795","display_name":"Yipan Song","orcid":null},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yipan Song","raw_affiliation_strings":["College of Computer and Information Science, Chongqing Normal University,China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Chongqing Normal University,China","institution_ids":["https://openalex.org/I126924076"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100723448","display_name":"Peilin Li","orcid":"https://orcid.org/0000-0003-0009-9082"},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peilin Li","raw_affiliation_strings":["College of Mathematical Sciences, Chongqing Normal University,China"],"affiliations":[{"raw_affiliation_string":"College of Mathematical Sciences, Chongqing Normal University,China","institution_ids":["https://openalex.org/I126924076"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124101112","display_name":"Weixiao Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixiao Dai","raw_affiliation_strings":["College of Computer and Information Science, Chongqing Normal University,China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Chongqing Normal University,China","institution_ids":["https://openalex.org/I126924076"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5095373071","display_name":"Ruisheng Ran","orcid":null},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruisheng Ran","raw_affiliation_strings":["College of Computer and Information Science, Chongqing Normal University,China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Chongqing Normal University,China","institution_ids":["https://openalex.org/I126924076"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126924076"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72885587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1515","last_page":"1521"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.47839999198913574,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.47839999198913574,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10106","display_name":"Autism Spectrum Disorder Research","score":0.23280000686645508,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.038100000470876694,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8055999875068665},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6686000227928162},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6126999855041504},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4950999915599823},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.4893999993801117},{"id":"https://openalex.org/keywords/riemannian-manifold","display_name":"Riemannian manifold","score":0.4747999906539917},{"id":"https://openalex.org/keywords/euclidean-space","display_name":"Euclidean space","score":0.42879998683929443},{"id":"https://openalex.org/keywords/positive-definite-matrix","display_name":"Positive-definite matrix","score":0.3944999873638153},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.3921000063419342},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.38359999656677246}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8055999875068665},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6686000227928162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6636000275611877},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6126999855041504},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4950999915599823},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.4893999993801117},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48750001192092896},{"id":"https://openalex.org/C2779593128","wikidata":"https://www.wikidata.org/wiki/Q632814","display_name":"Riemannian manifold","level":2,"score":0.4747999906539917},{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41260001063346863},{"id":"https://openalex.org/C49712288","wikidata":"https://www.wikidata.org/wiki/Q77601250","display_name":"Positive-definite matrix","level":3,"score":0.3944999873638153},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.3921000063419342},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.3418000042438507},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.3411000072956085},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.32899999618530273},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C153120616","wikidata":"https://www.wikidata.org/wiki/Q17068315","display_name":"Manifold alignment","level":4,"score":0.3188999891281128},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30660000443458557},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.29910001158714294},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2881999909877777},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C54848796","wikidata":"https://www.wikidata.org/wiki/Q339011","display_name":"Symmetric matrix","level":3,"score":0.2782999873161316},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2759999930858612},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C121705324","wikidata":"https://www.wikidata.org/wiki/Q1510587","display_name":"Pseudo-Riemannian manifold","level":4,"score":0.26249998807907104},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7545074820518494}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2008056655","https://openalex.org/W2460144244","https://openalex.org/W2517500902","https://openalex.org/W2551687757","https://openalex.org/W2779020697","https://openalex.org/W2991597748","https://openalex.org/W3091732964","https://openalex.org/W3095479837","https://openalex.org/W3155786160","https://openalex.org/W3175078852","https://openalex.org/W3209594421","https://openalex.org/W4229706427","https://openalex.org/W4289844328","https://openalex.org/W4309631262","https://openalex.org/W4311465618","https://openalex.org/W4378675345","https://openalex.org/W4393950167","https://openalex.org/W4400413155","https://openalex.org/W4402135883","https://openalex.org/W4402184853","https://openalex.org/W4404421877","https://openalex.org/W4406261453","https://openalex.org/W4406893029","https://openalex.org/W4409382615","https://openalex.org/W4412404004"],"related_works":[],"abstract_inverted_index":{"The":[0],"functional":[1,109],"connectivity":[2,110],"matrix":[3,31,111],"of":[4,16],"the":[5,108,113,127,146,158],"brain":[6,20],"is":[7,32],"a":[8,33,85,96,121],"commonly":[9],"used":[10],"representation":[11],"for":[12],"modeling":[13],"collaborative":[14],"relationships":[15],"neural":[17],"activity":[18],"between":[19],"regions,":[21],"widely":[22],"applied":[23],"in":[24,60,70,171],"research":[25],"on":[26,46,79,100,112,126,157],"autism":[27],"spectrum":[28],"disorder.":[29],"This":[30,93],"symmetric":[34,128],"positive":[35,129],"semidefinite":[36],"matrix,":[37],"including":[38],"complex":[39],"non-Euclidean":[40],"geometric":[41,55],"structures.":[42],"Traditional":[43],"methods":[44,66,170],"based":[45,99],"Euclidean":[47],"space":[48],"struggle":[49],"to":[50,102,132],"fully":[51],"capture":[52],"its":[53],"intrinsic":[54],"relationships,":[56],"limiting":[57],"further":[58],"improvements":[59],"model":[61,140],"performance.":[62],"In":[63],"addition,":[64],"previous":[65],"still":[67],"have":[68],"shortcomings":[69],"selecting":[71],"key":[72,172],"connections":[73],"and":[74,138,142,167,190,198],"compressing":[75],"redundant":[76],"information.":[77],"Based":[78],"these":[80],"issues,":[81],"this":[82],"paper":[83],"proposes":[84],"Riemannian":[86],"manifold":[87,131,168],"sparse":[88,123],"Siamese":[89,147],"autoencoder":[90,98],"(R-SSAE):":[91],"(1)":[92],"method":[94],"integrates":[95],"stacked":[97],"SPDNet":[101],"extract":[103],"deep":[104],"discriminative":[105,196],"features":[106],"from":[107],"Symmetric":[114],"Positive":[115],"Definite":[116],"manifold;":[117],"(2)":[118],"It":[119],"introduces":[120],"structured":[122],"regularization":[124],"mechanism":[125],"definite":[130],"enhance":[133],"critical":[134],"connection":[135],"identification":[136],"capabilities":[137],"improve":[139],"robustness;":[141],"(3)":[143],"By":[144],"incorporating":[145],"network,":[148],"it":[149],"effectively":[150],"captures":[151],"subtle":[152],"individual":[153],"differences.":[154],"Experimental":[155],"results":[156],"ABIDE":[159],"dataset":[160],"demonstrate":[161],"that":[162],"R-SSAE":[163],"outperforms":[164],"existing":[165],"Euclidean-based":[166],"learning":[169],"metrics":[173],"such":[174],"as":[175],"accuracy":[176],"<tex":[177,182],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[178,183],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$(75.33":[179],"\\%)$</tex>,":[180,185],"precision":[181],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$(75.44":[184],"F1":[186],"score":[187],"(73.50":[188],"%),":[189,193],"AUC":[191],"(80.01":[192],"exhibiting":[194],"superior":[195],"capability":[197],"robustness.":[199]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2026-01-30T00:00:00"}
