{"id":"https://openalex.org/W4206187231","doi":"https://doi.org/10.1109/bibm52615.2021.9669849","title":"A Graph Attention Neural Network for Diagnosing ASD with fMRI Data","display_name":"A Graph Attention Neural Network for Diagnosing ASD with fMRI Data","publication_year":2021,"publication_date":"2021-12-09","ids":{"openalex":"https://openalex.org/W4206187231","doi":"https://doi.org/10.1109/bibm52615.2021.9669849"},"language":"en","primary_location":{"id":"doi:10.1109/bibm52615.2021.9669849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669849","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5062733657","display_name":"Wutao Yin","orcid":"https://orcid.org/0000-0002-4530-2956"},"institutions":[{"id":"https://openalex.org/I32625721","display_name":"University of Saskatchewan","ror":"https://ror.org/010x8gc63","country_code":"CA","type":"education","lineage":["https://openalex.org/I32625721"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Wutao Yin","raw_affiliation_strings":["Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, Canada"],"affiliations":[{"raw_affiliation_string":"Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, Canada","institution_ids":["https://openalex.org/I32625721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004606852","display_name":"Longhai Li","orcid":"https://orcid.org/0000-0002-3074-8584"},"institutions":[{"id":"https://openalex.org/I32625721","display_name":"University of Saskatchewan","ror":"https://ror.org/010x8gc63","country_code":"CA","type":"education","lineage":["https://openalex.org/I32625721"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Longhai Li","raw_affiliation_strings":["Dept. of Mathematics and Statistics, University of Saskatchewan, Saskatoon, Cananda"],"affiliations":[{"raw_affiliation_string":"Dept. of Mathematics and Statistics, University of Saskatchewan, Saskatoon, Cananda","institution_ids":["https://openalex.org/I32625721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091157395","display_name":"Fang\u2010Xiang Wu","orcid":"https://orcid.org/0000-0002-4593-9332"},"institutions":[{"id":"https://openalex.org/I32625721","display_name":"University of Saskatchewan","ror":"https://ror.org/010x8gc63","country_code":"CA","type":"education","lineage":["https://openalex.org/I32625721"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fang-Xiang Wu","raw_affiliation_strings":["Dept. of Mechanical Engr., Div. of Biomedical Engr., University of Saskatchewan, Saskatoon, SK, Canada"],"affiliations":[{"raw_affiliation_string":"Dept. of Mechanical Engr., Div. of Biomedical Engr., University of Saskatchewan, Saskatoon, SK, Canada","institution_ids":["https://openalex.org/I32625721"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062733657"],"corresponding_institution_ids":["https://openalex.org/I32625721"],"apc_list":null,"apc_paid":null,"fwci":3.0007,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.94504505,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1131","last_page":"1136"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9998000264167786,"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":0.9998000264167786,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9976000189781189,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9765999913215637,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.7042014598846436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6970888376235962},{"id":"https://openalex.org/keywords/autism-spectrum-disorder","display_name":"Autism spectrum disorder","score":0.5704689621925354},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.5359936952590942},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.517099142074585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5169453024864197},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.4944767951965332},{"id":"https://openalex.org/keywords/resting-state-fmri","display_name":"Resting state fMRI","score":0.49283623695373535},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4680699110031128},{"id":"https://openalex.org/keywords/power-graph-analysis","display_name":"Power graph analysis","score":0.4301200211048126},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42444485425949097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3849713206291199},{"id":"https://openalex.org/keywords/autism","display_name":"Autism","score":0.330666184425354},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.24441498517990112},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.21599283814430237},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1737927794456482},{"id":"https://openalex.org/keywords/psychiatry","display_name":"Psychiatry","score":0.12669673562049866}],"concepts":[{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.7042014598846436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6970888376235962},{"id":"https://openalex.org/C2778538070","wikidata":"https://www.wikidata.org/wiki/Q1436063","display_name":"Autism spectrum disorder","level":3,"score":0.5704689621925354},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.5359936952590942},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.517099142074585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5169453024864197},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.4944767951965332},{"id":"https://openalex.org/C66324658","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Resting state fMRI","level":2,"score":0.49283623695373535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4680699110031128},{"id":"https://openalex.org/C106937863","wikidata":"https://www.wikidata.org/wiki/Q7236518","display_name":"Power graph analysis","level":3,"score":0.4301200211048126},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42444485425949097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3849713206291199},{"id":"https://openalex.org/C205778803","wikidata":"https://www.wikidata.org/wiki/Q38404","display_name":"Autism","level":2,"score":0.330666184425354},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.24441498517990112},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.21599283814430237},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1737927794456482},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.12669673562049866},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm52615.2021.9669849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669849","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334971","display_name":"Science and Engineering Research Council","ror":"https://ror.org/00zgdb249"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1457602677","https://openalex.org/W1980309199","https://openalex.org/W2013016035","https://openalex.org/W2030902100","https://openalex.org/W2054924908","https://openalex.org/W2089572795","https://openalex.org/W2092655084","https://openalex.org/W2117140276","https://openalex.org/W2120759354","https://openalex.org/W2122457251","https://openalex.org/W2168424072","https://openalex.org/W2314945771","https://openalex.org/W2533800772","https://openalex.org/W2746329898","https://openalex.org/W2752558629","https://openalex.org/W2789863594","https://openalex.org/W2806614401","https://openalex.org/W2886989735","https://openalex.org/W2891131577","https://openalex.org/W2907492528","https://openalex.org/W2913713055","https://openalex.org/W2962711740","https://openalex.org/W2963303578","https://openalex.org/W2964877070","https://openalex.org/W2972996185","https://openalex.org/W2977883299","https://openalex.org/W2990504128","https://openalex.org/W3020893582","https://openalex.org/W3093225483","https://openalex.org/W3095114157","https://openalex.org/W3112948680","https://openalex.org/W3152893301","https://openalex.org/W3194414692","https://openalex.org/W4286795917","https://openalex.org/W4295312788","https://openalex.org/W4297733535","https://openalex.org/W6754929296","https://openalex.org/W6766978945","https://openalex.org/W6776429975","https://openalex.org/W6784418995","https://openalex.org/W6797464607"],"related_works":["https://openalex.org/W2601707947","https://openalex.org/W2168298321","https://openalex.org/W2387620927","https://openalex.org/W2294986132","https://openalex.org/W2365936003","https://openalex.org/W4401572343","https://openalex.org/W2790620361","https://openalex.org/W1964455563","https://openalex.org/W2319066238","https://openalex.org/W2371524820"],"abstract_inverted_index":{"Autism":[0],"Spectrum":[1],"Disorder":[2],"(ASD)":[3],"is":[4,25,61,184],"a":[5,128,162],"common":[6,29],"psychiatric":[7],"disorder":[8],"disease":[9],"that":[10,90,217],"typically":[11],"causes":[12],"impaired":[13],"communication":[14],"and":[15,42,70,154,160],"compromised":[16],"social":[17],"interactions.":[18],"Functional":[19],"magnetic":[20],"resonance":[21],"imaging":[22],"(fMRI)":[23],"data":[24,60,168],"one":[26],"of":[27,44,52,94,102,106,156,195,207],"the":[28,40,76,92,100,187,193,201,205],"neuroimaging":[30],"modalities":[31],"for":[32,134,166,224],"understanding":[33],"human":[34],"brain":[35,45,188],"functionalities":[36],"as":[37,39,109],"well":[38],"diagnosis":[41,136],"treatment":[43],"disorders.":[46],"There":[47],"are":[48,87],"many":[49,119],"successful":[50],"applications":[51],"deep":[53],"learning":[54,121],"to":[55,176,204],"fMRI":[56,59,145,157,167,228],"analytics":[57],"where":[58],"mostly":[62],"considered":[63],"structured":[64],"Euclidean":[65],"grids":[66],"or":[67,79],"time":[68,80,158],"series,":[69],"features":[71,223],"were":[72],"usually":[73],"extracted":[74],"from":[75,143,211],"computer":[77],"vision":[78],"series":[81,159],"perspective.":[82],"Graph":[83],"neural":[84,88],"networks":[85,89],"(GNNs)":[86],"learn":[91],"interactions":[93],"graphs":[95,149],"via":[96],"message":[97],"passing":[98],"between":[99],"nodes":[101],"graphs.":[103],"Recently":[104],"variants":[105],"GNNs":[107],"such":[108],"graph":[110,131],"attention":[111,132],"network":[112,133],"(GAT)":[113],"have":[114],"demonstrated":[115],"outstanding":[116],"performances":[117],"on":[118,151],"machine":[120],"tasks.":[122],"In":[123],"this":[124],"paper,":[125],"we":[126,199],"proposed":[127,197],"connectivity":[129,139],"based":[130,150,172],"autism":[135],"using":[137],"functional":[138,189],"(FC)":[140],"patterns":[141],"obtained":[142],"resting-state":[144],"(rs-fMRI).":[146],"We":[147],"define":[148],"F":[152],"Cs":[153],"statistics":[155],"present":[161],"connectivity-based":[163],"GATs":[164],"model":[165,203],"analysis.":[169,229],"The":[170],"graph-theoretic":[171],"approach":[173],"enables":[174],"us":[175],"pass":[177],"messages":[178],"among":[179],"connectomic":[180],"(Non-Euclidean)":[181],"neighborhoods,":[182],"which":[183],"consistent":[185],"with":[186],"networks.":[190],"To":[191],"evaluate":[192],"performance":[194],"our":[196],"GAT,":[198],"apply":[200],"GAT":[202,218],"classification":[206],"A":[208],"SD":[209],"patients":[210],"normal":[212],"controls.":[213],"Our":[214],"results":[215],"show":[216],"can":[219],"effectively":[220],"capture":[221],"salient":[222],"ASD":[225],"classifications":[226],"in":[227]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}