{"id":"https://openalex.org/W4320024280","doi":"https://doi.org/10.1109/bigdata55660.2022.10020314","title":"Pre-train Graph Neural Networks for Brain Network Analysis (Extended Abstract)","display_name":"Pre-train Graph Neural Networks for Brain Network Analysis (Extended Abstract)","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4320024280","doi":"https://doi.org/10.1109/bigdata55660.2022.10020314"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020314","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"2022 IEEE International Conference on Big Data (Big Data)","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/A5001975694","display_name":"Yi Yang","orcid":"https://orcid.org/0000-0002-5599-0975"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yi Yang","raw_affiliation_strings":["Emory University,Department of Computer Science,Atlanta,GA,United States","Department of Computer Science, Emory University, Atlanta, GA, United States"],"affiliations":[{"raw_affiliation_string":"Emory University,Department of Computer Science,Atlanta,GA,United States","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Department of Computer Science, Emory University, Atlanta, GA, United States","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033157677","display_name":"Hejie Cui","orcid":"https://orcid.org/0000-0001-6388-2619"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hejie Cui","raw_affiliation_strings":["Emory University,Department of Computer Science,Atlanta,GA,United States","Department of Computer Science, Emory University, Atlanta, GA, United States"],"affiliations":[{"raw_affiliation_string":"Emory University,Department of Computer Science,Atlanta,GA,United States","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Department of Computer Science, Emory University, Atlanta, GA, United States","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006897094","display_name":"Carl Yang","orcid":"https://orcid.org/0000-0001-9145-4531"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carl Yang","raw_affiliation_strings":["Emory University,Department of Computer Science,Atlanta,GA,United States","Department of Computer Science, Emory University, Atlanta, GA, United States"],"affiliations":[{"raw_affiliation_string":"Emory University,Department of Computer Science,Atlanta,GA,United States","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Department of Computer Science, Emory University, Atlanta, GA, United States","institution_ids":["https://openalex.org/I150468666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5001975694"],"corresponding_institution_ids":["https://openalex.org/I150468666"],"apc_list":null,"apc_paid":null,"fwci":1.8129,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.8806752,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4993","last_page":"4994"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.996399998664856,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9908000230789185,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7645347118377686},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.5907430052757263},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5652061700820923},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5337458848953247},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5133323073387146},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48418763279914856},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45578545331954956},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4283732771873474},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.4238487780094147},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.18545067310333252},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.12494388222694397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7645347118377686},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.5907430052757263},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5652061700820923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5337458848953247},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5133323073387146},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48418763279914856},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45578545331954956},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4283732771873474},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.4238487780094147},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.18545067310333252},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.12494388222694397},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020314","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2088272457","https://openalex.org/W3035524453","https://openalex.org/W3036446966","https://openalex.org/W3099152386","https://openalex.org/W3105762472","https://openalex.org/W4290877635","https://openalex.org/W6726873649","https://openalex.org/W6736057607","https://openalex.org/W6754929296","https://openalex.org/W6755573351","https://openalex.org/W6766156693","https://openalex.org/W6767288045","https://openalex.org/W6772452955","https://openalex.org/W6782886300","https://openalex.org/W6841246528"],"related_works":["https://openalex.org/W2327340211","https://openalex.org/W2027542625","https://openalex.org/W4292199793","https://openalex.org/W2282195379","https://openalex.org/W2295388821","https://openalex.org/W2102312026","https://openalex.org/W2885663991","https://openalex.org/W2071433170","https://openalex.org/W2089784006","https://openalex.org/W1016623679"],"abstract_inverted_index":{"Human":[0],"brains,":[1],"controlling":[2],"behaviors":[3],"and":[4,18,39,85,125],"cognition,":[5],"are":[6,33,53,93,115,153],"at":[7],"the":[8,57,80,138],"center":[9],"of":[10,30,59,64,75,100,144],"complex":[11],"neurobiological":[12],"systems.":[13,197],"Recent":[14],"studies":[15,172,193],"in":[16,214],"neuroscience":[17],"neuroimaging":[19],"analysis":[20,58],"have":[21],"reached":[22],"a":[23,46,72,181],"consensus":[24],"that":[25,152],"interactions":[26],"among":[27],"brain":[28,60,90,140,170],"regions":[29],"interest":[31],"(ROIs)":[32],"driving":[34],"factors":[35],"for":[36,49,148],"neural":[37,42],"development":[38],"disorders.":[40],"Graph":[41],"networks":[43],"(GNNs)":[44],"as":[45,216,218],"powerful":[47],"tool":[48],"analyzing":[50],"graph-structured":[51],"data":[52,82,88],"naturally":[54],"applied":[55],"to":[56,79,97,133,136,156,167,187],"networks.":[61],"However,":[62],"training":[63],"deep":[65],"learning":[66],"models":[67,151],"including":[68],"GNNs":[69],"often":[70,116],"requires":[71],"significant":[73],"amount":[74],"labeled":[76],"data.":[77],"Due":[78],"complicated":[81],"acquisition":[83],"process":[84],"restrictions":[86],"on":[87,118],"sharing,":[89],"network":[91,141],"datasets":[92,120],"still":[94],"small":[95],"compared":[96],"other":[98],"types":[99],"graphs":[101],"(e.g.,":[102,111],"social":[103],"networks,":[104],"molecules,":[105],"proteins).":[106],"Moreover,":[107],"real":[108],"clinical":[109,146],"tasks":[110],"mental":[112],"disorder":[113],"analysis)":[114],"conducted":[117],"local":[119],"with":[121,194,203,207],"even":[122],"smaller":[123],"scales":[124],"larger":[126],"noises.":[127],"To":[128],"this":[129],"end,":[130],"we":[131,161,179],"propose":[132],"leverage":[134],"pre-training":[135,165],"capture":[137],"intrinsic":[139],"structures":[142],"regardless":[143],"specific":[145],"outcomes,":[147],"obtaining":[149],"GNN":[150,205],"easily":[154],"adaptable":[155],"downstream":[157],"tasks.":[158],"Specifically,":[159],"(1)":[160],"design":[162],"brain-network-oriented":[163],"unsupervised":[164],"techniques":[166],"utilize":[168],"large-scale":[169],"imaging":[171],"without":[173],"highly":[174],"relevant":[175],"task":[176],"labels;":[177],"(2)":[178],"develop":[180],"data-driven":[182],"parcellation":[183],"atlas":[184],"mapping":[185],"pipeline":[186],"facilitate":[188],"effective":[189],"knowledge":[190],"transfer":[191],"across":[192],"different":[195],"ROI":[196],"The":[198],"proposed":[199],"framework":[200],"is":[201],"validated":[202],"various":[204],"models,":[206],"extensive":[208],"empirical":[209],"results":[210],"demonstrating":[211],"consistent":[212],"improvement":[213],"performance":[215],"well":[217],"robustness.":[219]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-02T06:13:33.250793","created_date":"2025-10-10T00:00:00"}
