{"id":"https://openalex.org/W7171559388","doi":"https://doi.org/10.1145/3807503.3819467","title":"Multimodal Fusion and Adaptive Learning for Cardiopulmonary Classification","display_name":"Multimodal Fusion and Adaptive Learning for Cardiopulmonary Classification","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7171559388","doi":"https://doi.org/10.1145/3807503.3819467"},"language":null,"primary_location":{"id":"doi:10.1145/3807503.3819467","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807503.3819467","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3807503.3819467","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052566458","display_name":"Mahjabeen Tamanna Abed","orcid":null},"institutions":[{"id":"https://openalex.org/I137317281","display_name":"Washington State University Vancouver","ror":"https://ror.org/00g2fk805","country_code":"US","type":"education","lineage":["https://openalex.org/I137317281","https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahjabeen Tamanna Abed","raw_affiliation_strings":["Washington State University, Vancouver, WA, USA"],"raw_orcid":"https://orcid.org/0009-0009-6190-0022","affiliations":[{"raw_affiliation_string":"Washington State University, Vancouver, WA, USA","institution_ids":["https://openalex.org/I137317281"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007023851","display_name":"Xinghui Zhao","orcid":"https://orcid.org/0000-0002-5120-0972"},"institutions":[{"id":"https://openalex.org/I137317281","display_name":"Washington State University Vancouver","ror":"https://ror.org/00g2fk805","country_code":"US","type":"education","lineage":["https://openalex.org/I137317281","https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinghui Zhao","raw_affiliation_strings":["Washington State University, Vancouver, WA, USA"],"raw_orcid":"https://orcid.org/0000-0002-5120-0972","affiliations":[{"raw_affiliation_string":"Washington State University, Vancouver, WA, USA","institution_ids":["https://openalex.org/I137317281"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I137317281"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.31709998846054077},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.30239999294281006},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.29600000381469727},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2815999984741211},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.2655999958515167}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5938000082969666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5516999959945679},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32910001277923584},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2574000060558319}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3807503.3819467","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807503.3819467","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3807503.3819467","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807503.3819467","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1587447546","https://openalex.org/W1989085630","https://openalex.org/W2151194828","https://openalex.org/W2515753980","https://openalex.org/W2619383789","https://openalex.org/W2781924583","https://openalex.org/W2963192057","https://openalex.org/W2963466845","https://openalex.org/W2995225687","https://openalex.org/W3106717751","https://openalex.org/W3153585807","https://openalex.org/W4213439844","https://openalex.org/W4298007628","https://openalex.org/W4308885870","https://openalex.org/W4313439128","https://openalex.org/W4389571280","https://openalex.org/W4395037541","https://openalex.org/W4401076673","https://openalex.org/W4401540543","https://openalex.org/W4402536012","https://openalex.org/W7103756088"],"related_works":[],"abstract_inverted_index":{"Cardiovascular":[0],"diseases":[1],"remain":[2],"a":[3],"leading":[4,9],"cause":[5],"of":[6,24,40,90],"mortality":[7],"worldwide,":[8],"to":[10,34,53,72,87],"the":[11,22,36,44,67,88],"urgent":[12],"need":[13],"for":[14,30],"intelligent,":[15],"real-time":[16],"diagnostic":[17],"systems.":[18],"This":[19],"paper":[20],"proposes":[21],"development":[23],"an":[25],"adaptive":[26,50],"multimodal":[27,103],"learning":[28,48],"framework":[29],"heart":[31],"monitoring,":[32],"aiming":[33],"enhance":[35],"accuracy":[37],"and":[38,49,98],"responsiveness":[39],"cardiac":[41,100],"diagnosis.":[42],"Specifically,":[43],"system":[45],"leverages":[46],"deep":[47],"fusion":[51],"techniques":[52],"support":[54],"effective":[55],"diagnosis":[56],"by":[57,94],"integrating":[58],"heterogeneous":[59],"data":[60],"sources.":[61],"Our":[62],"experimental":[63],"results":[64],"show":[65],"that":[66],"proposed":[68],"approach":[69],"can":[70],"lead":[71],"improved":[73],"robustness":[74],"when":[75],"multiple":[76],"patient":[77],"modalities":[78],"are":[79],"used":[80],"as":[81],"input.":[82],"Ultimately,":[83],"this":[84],"research":[85],"contributes":[86],"advancement":[89],"smart":[91],"healthcare":[92],"technology":[93],"enabling":[95],"proactive,":[96],"personalized,":[97],"resilient":[99],"care":[101],"through":[102],"intelligence.":[104]},"counts_by_year":[],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2026-07-29T00:00:00"}
