{"id":"https://openalex.org/W7113903564","doi":"https://doi.org/10.1145/3765612.3767226","title":"ATHENA: Atherosclerosis through Hierarchical Explainable Neural Network Analysis","display_name":"ATHENA: Atherosclerosis through Hierarchical Explainable Neural Network Analysis","publication_year":2025,"publication_date":"2025-10-12","ids":{"openalex":"https://openalex.org/W7113903564","doi":"https://doi.org/10.1145/3765612.3767226"},"language":null,"primary_location":{"id":"doi:10.1145/3765612.3767226","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3765612.3767226","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3765612.3767226","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Irsyad Adam","orcid":"https://orcid.org/0009-0000-2288-401X"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Irsyad Adam","raw_affiliation_strings":["DGSOM, University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"DGSOM, University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Steven Swee","orcid":"https://orcid.org/0009-0003-8038-6512"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven Swee","raw_affiliation_strings":["DGSOM, University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"DGSOM, University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Erika Yilin Zheng","orcid":"https://orcid.org/0009-0001-5319-3593"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Erika Yilin Zheng","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ethan Ji","orcid":"https://orcid.org/0009-0006-3663-9211"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ethan Ji","raw_affiliation_strings":["DGSOM, University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"DGSOM, University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"William Speier","orcid":"https://orcid.org/0000-0002-0890-8684"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William Speier","raw_affiliation_strings":["DGSOM, University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"DGSOM, University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ding Wang","orcid":"https://orcid.org/0000-0001-8236-8551"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ding Wang","raw_affiliation_strings":["DGSOM, University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"DGSOM, University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Alex Bui","orcid":"https://orcid.org/0000-0002-4702-1373"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alex Bui","raw_affiliation_strings":["DGSOM, University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"DGSOM, University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-8180-2886"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["Computer Science, University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science, University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Karol Watson","orcid":"https://orcid.org/0000-0003-3658-6165"},"institutions":[{"id":"https://openalex.org/I2799798094","display_name":"UCLA Health","ror":"https://ror.org/01d88se56","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2799798094"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karol Watson","raw_affiliation_strings":["DGSOM, UCLA Health, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"DGSOM, UCLA Health, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I2799798094"]}]},{"author_position":"last","author":{"id":null,"display_name":"Peipei Ping","orcid":"https://orcid.org/0000-0003-3583-3881"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peipei Ping","raw_affiliation_strings":["DGSOM, University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"DGSOM, University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80151338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.336899995803833,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.336899995803833,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.11580000072717667,"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/T12955","display_name":"Atherosclerosis and Cardiovascular Diseases","score":0.05689999833703041,"subfield":{"id":"https://openalex.org/subfields/2403","display_name":"Immunology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.525600016117096},{"id":"https://openalex.org/keywords/subnetwork","display_name":"Subnetwork","score":0.5103999972343445},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.49390000104904175},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43050000071525574},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42890000343322754},{"id":"https://openalex.org/keywords/data-integration","display_name":"Data integration","score":0.37700000405311584},{"id":"https://openalex.org/keywords/personalized-medicine","display_name":"Personalized medicine","score":0.3653999865055084},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.36329999566078186},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.36000001430511475}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5907999873161316},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.525600016117096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5152999758720398},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.5103999972343445},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.49390000104904175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4399000108242035},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43050000071525574},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42890000343322754},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C32220436","wikidata":"https://www.wikidata.org/wiki/Q2072214","display_name":"Personalized medicine","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.36329999566078186},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3546999990940094},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.31779998540878296},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29159998893737793},{"id":"https://openalex.org/C3019692148","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Therapeutic modalities","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.2766999900341034},{"id":"https://openalex.org/C3018605307","wikidata":"https://www.wikidata.org/wiki/Q200779","display_name":"Complex disease","level":3,"score":0.26589998602867126},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C3020646490","wikidata":"https://www.wikidata.org/wiki/Q25203551","display_name":"Clinical phenotype","level":4,"score":0.2612000107765198},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3765612.3767226","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3765612.3767226","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3765612.3767226","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3765612.3767226","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1968504368","https://openalex.org/W1980465014","https://openalex.org/W1991638553","https://openalex.org/W2001669885","https://openalex.org/W2041711147","https://openalex.org/W2055041166","https://openalex.org/W2135871219","https://openalex.org/W2157894862","https://openalex.org/W2316167515","https://openalex.org/W2783058208","https://openalex.org/W2797870555","https://openalex.org/W2805484788","https://openalex.org/W2951029718","https://openalex.org/W3156270925","https://openalex.org/W3168285879","https://openalex.org/W4206776774","https://openalex.org/W4296780664","https://openalex.org/W4392741075","https://openalex.org/W4394691051","https://openalex.org/W4396919023","https://openalex.org/W4398781455","https://openalex.org/W4404511387","https://openalex.org/W4410942180","https://openalex.org/W4411167469"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1,161,229],"work,":[2],"we":[3,99,158],"study":[4],"the":[5,33,36,188,239],"problem":[6],"pertaining":[7],"to":[8,22,42,183],"personalized":[9,234],"classification":[10,50,176],"of":[11,27,35,89,142,164,241,247],"subclinical":[12,174],"atherosclerosis":[13,175,208],"by":[14,181],"developing":[15],"a":[16,28,111,138,203],"hierarchical":[17,113],"graph":[18],"neural":[19],"network":[20,114],"framework":[21,232],"leverage":[23],"two":[24],"characteristic":[25],"modalities":[26],"patient:":[29],"clinical":[30,82,140,165,205,249],"features":[31,166],"within":[32],"context":[34],"cohort,":[37],"and":[38,58,193,211,245],"molecular":[39,53,125,168],"data":[40],"unique":[41],"individual":[43,129],"patients.":[44,94],"Current":[45],"graph-based":[46],"methods":[47],"for":[48,68],"disease":[49,243],"detect":[51],"patient-specific":[52,124],"fingerprints,":[54],"but":[55],"lack":[56],"consistency":[57,133],"comprehension":[59],"regarding":[60],"cohort-wide":[61,135],"features,":[62],"which":[63,109],"are":[64],"an":[65],"essential":[66],"requirement":[67],"understanding":[69,77],"pathogenic":[70,91],"phenotypes":[71],"across":[72,178],"diverse":[73],"atherosclerotic":[74,242],"trajectories.":[75],"Furthermore,":[76],"patient":[78,220],"subtypes":[79],"often":[80],"considers":[81],"feature":[83],"similarity":[84],"in":[85,185,195],"isolation,":[86],"without":[87],"integration":[88,231],"shared":[90],"interdependencies":[92],"among":[93],"To":[95],"address":[96],"these":[97],"challenges,":[98],"introduce":[100],"ATHENA:":[101],"Atherosclerosis":[102],"Through":[103],"Hierarchical":[104],"Explainable":[105],"Neural":[106],"Network":[107],"Analysis,":[108],"constructs":[110],"novel":[112,230],"representation":[115],"through":[116,223],"integrated":[117],"modality":[118],"learning;":[119],"subsequently,":[120],"it":[121],"optimizes":[122],"learned":[123],"finger-prints":[126],"that":[127,160],"reflect":[128],"omics":[130],"data,":[131],"enforcing":[132],"with":[134,167],"patterns.":[136],"With":[137],"primary":[139],"dataset":[141,206],"391":[143],"patients":[144],"(PESA":[145],"study),":[146],"their":[147,154,248],"respective":[148],"transcriptomics":[149],"signatures,":[150],"as":[151,153],"well":[152],"STRING":[155],"PPI":[156],"profiles,":[157],"demonstrate":[159],"heterogeneous":[162],"alignment":[163],"interaction":[169],"patterns":[170],"has":[171],"significantly":[172],"boosted":[173],"performance":[177],"various":[179],"baselines":[180],"up":[182],"13%":[184],"area":[186],"under":[187],"receiver":[189],"operating":[190],"curve":[191],"(AUC)":[192],"20%":[194],"F1":[196],"score.":[197],"We":[198],"further":[199],"validated":[200],"ATHENA":[201,217],"on":[202,207],"secondary":[204],"(by":[209],"Steenman":[210],"Espitia":[212],"et":[213],"al.).":[214],"Taken":[215],"together,":[216],"enables":[218],"mechanistically-informed":[219],"subtype":[221],"discovery":[222],"explainable":[224],"AI":[225],"(XAI)-driven":[226],"subnetwork":[227],"clustering;":[228],"strengthens":[233],"intervention":[235],"strategies,":[236],"thereby":[237],"improving":[238],"prediction":[240],"progression":[244],"management":[246],"actionable":[250],"outcomes.":[251]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-12-11T00:00:00"}