{"id":"https://openalex.org/W4399144492","doi":"https://doi.org/10.1145/3654823.3654855","title":"Detection of Venous Thromboembolism Using Recurrent Neural Networks with Time-Series Data","display_name":"Detection of Venous Thromboembolism Using Recurrent Neural Networks with Time-Series Data","publication_year":2024,"publication_date":"2024-03-22","ids":{"openalex":"https://openalex.org/W4399144492","doi":"https://doi.org/10.1145/3654823.3654855"},"language":"en","primary_location":{"id":"doi:10.1145/3654823.3654855","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","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/A5026647002","display_name":"Can Xu","orcid":"https://orcid.org/0000-0002-5103-8688"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Can Xu","raw_affiliation_strings":["The Institution of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, China"],"raw_orcid":"https://orcid.org/0000-0002-5103-8688","affiliations":[{"raw_affiliation_string":"The Institution of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084698290","display_name":"Yaqin Huang","orcid":"https://orcid.org/0009-0006-3761-3179"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]},{"id":"https://openalex.org/I4210154480","display_name":"Chongqing Cancer Hospital","ror":"https://ror.org/047d8yx24","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210154480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaqin Huang","raw_affiliation_strings":["Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, China"],"raw_orcid":"https://orcid.org/0009-0006-3761-3179","affiliations":[{"raw_affiliation_string":"Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, China","institution_ids":["https://openalex.org/I4210154480","https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101479167","display_name":"Xinni Xiang","orcid":"https://orcid.org/0000-0002-1291-0947"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinni Xiang","raw_affiliation_strings":["West China School of Medicine, West China Hospital, Sichuan University, China"],"raw_orcid":"https://orcid.org/0000-0002-1291-0947","affiliations":[{"raw_affiliation_string":"West China School of Medicine, West China Hospital, Sichuan University, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053547514","display_name":"Haike Lei","orcid":"https://orcid.org/0000-0003-0284-2052"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]},{"id":"https://openalex.org/I4210154480","display_name":"Chongqing Cancer Hospital","ror":"https://ror.org/047d8yx24","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210154480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haike Lei","raw_affiliation_strings":["Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, China"],"raw_orcid":"https://orcid.org/0000-0003-0284-2052","affiliations":[{"raw_affiliation_string":"Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, China","institution_ids":["https://openalex.org/I4210154480","https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100404947","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0003-4801-7162"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Yang","raw_affiliation_strings":["The Institution of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, China"],"raw_orcid":"https://orcid.org/0000-0003-4801-7162","affiliations":[{"raw_affiliation_string":"The Institution of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5026647002"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17632766,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"170","last_page":"175"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10285","display_name":"Venous Thromboembolism Diagnosis and Management","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2724","display_name":"Internal Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10285","display_name":"Venous Thromboembolism Diagnosis and Management","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2724","display_name":"Internal Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10227","display_name":"Acute Ischemic Stroke Management","score":0.927299976348877,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10292","display_name":"Acute Myocardial Infarction Research","score":0.9103999733924866,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6799895763397217},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5855175852775574},{"id":"https://openalex.org/keywords/venous-thromboembolism","display_name":"Venous thromboembolism","score":0.5603834986686707},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.524039089679718},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5152142643928528},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5047346353530884},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4879967272281647},{"id":"https://openalex.org/keywords/time-point","display_name":"Time point","score":0.4690350294113159},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.45143938064575195},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4369134306907654},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4334469437599182},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21711242198944092},{"id":"https://openalex.org/keywords/surgery","display_name":"Surgery","score":0.11125954985618591}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6799895763397217},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5855175852775574},{"id":"https://openalex.org/C2991741193","wikidata":"https://www.wikidata.org/wiki/Q2751330","display_name":"Venous thromboembolism","level":3,"score":0.5603834986686707},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.524039089679718},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5152142643928528},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5047346353530884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4879967272281647},{"id":"https://openalex.org/C2779466056","wikidata":"https://www.wikidata.org/wiki/Q107630651","display_name":"Time point","level":2,"score":0.4690350294113159},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.45143938064575195},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4369134306907654},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4334469437599182},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21711242198944092},{"id":"https://openalex.org/C141071460","wikidata":"https://www.wikidata.org/wiki/Q40821","display_name":"Surgery","level":1,"score":0.11125954985618591},{"id":"https://openalex.org/C2780868729","wikidata":"https://www.wikidata.org/wiki/Q261327","display_name":"Thrombosis","level":2,"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/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3654823.3654855","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W2110485445","https://openalex.org/W2166345657","https://openalex.org/W2754231183","https://openalex.org/W2767014232","https://openalex.org/W2897821359","https://openalex.org/W2906737995","https://openalex.org/W2911964244","https://openalex.org/W2970413753","https://openalex.org/W2997947674","https://openalex.org/W3000753279","https://openalex.org/W3007838157","https://openalex.org/W3020785432","https://openalex.org/W3023402713","https://openalex.org/W3025011581","https://openalex.org/W3034342478","https://openalex.org/W3037765194","https://openalex.org/W3089168916","https://openalex.org/W3129261127","https://openalex.org/W3133631487","https://openalex.org/W3163159417","https://openalex.org/W3202456239","https://openalex.org/W3210574730","https://openalex.org/W4205283523","https://openalex.org/W4231447736","https://openalex.org/W4299689471"],"related_works":["https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W4225394202","https://openalex.org/W3036642985","https://openalex.org/W3032952384","https://openalex.org/W2964335273","https://openalex.org/W2982145560","https://openalex.org/W2081900870","https://openalex.org/W1535949710"],"abstract_inverted_index":{"Machine":[0],"Learning":[1],"(ML)":[2],"has":[3,30,55,63],"been":[4,56],"widely":[5],"applied":[6],"to":[7,70,142],"medical":[8],"science":[9],"for":[10],"decades.":[11],"As":[12],"common":[13],"knowledge,":[14],"the":[15,40,81,85,99],"progress":[16],"of":[17,33,51,87,104,118,128,146,161,165],"many":[18,59],"diseases":[19],"is":[20,174],"often":[21,90],"chronic":[22],"and":[23,74,89,139,196,204],"dynamic.":[24],"Longitudinal":[25],"data,":[26,29,96],"or":[27],"time-series":[28,123],"better":[31],"descriptions":[32],"certain":[34],"diseases,":[35],"as":[36,47,98],"it":[37],"naturally":[38],"captures":[39],"dynamic":[41,82,120],"over":[42],"time.":[43],"Venous":[44],"thromboembolism":[45],"(VTE),":[46],"a":[48,111,129,154,198],"regular":[49],"complication":[50],"cancer":[52],"tumour":[53],"treatments,":[54],"emphasized":[57],"in":[58,182],"studies.":[60,185],"Recent":[61],"research":[62],"shown":[64],"that":[65,115,157,189],"ML":[66,180],"algorithms":[67],"incredibly":[68],"contribute":[69],"VTE":[71,112,184],"risk":[72],"estimation":[73],"prediction.":[75],"However,":[76],"existing":[77],"methods":[78],"rarely":[79],"consider":[80],"changes":[83],"during":[84],"development":[86],"VTE,":[88],"make":[91],"decisions":[92],"based":[93,134],"on":[94,153],"time-point":[95],"such":[97],"latest":[100],"blood":[101,162],"test":[102,149,163],"results":[103,164,187],"patients.":[105,147],"In":[106],"this":[107],"paper,":[108],"we":[109],"propose":[110],"detection":[113],"model":[114,126,152,191],"takes":[116],"advantage":[117],"capturing":[119],"information":[121],"using":[122],"data.":[124],"The":[125,172,186],"consists":[127],"Recurrent":[130],"Neural":[131],"Network":[132],"(RNN)":[133],"framework":[135],"with":[136,168,176,201],"time":[137],"embedding":[138],"Attention":[140],"mechanism":[141],"encode":[143],"longitudinal":[144],"features":[145],"We":[148],"our":[150,190],"proposed":[151],"real-world":[155],"dataset":[156],"contains":[158],"multiple":[159],"times":[160],"patients":[166],"together":[167],"other":[169],"clinical":[170],"features.":[171],"network":[173],"compared":[175],"several":[177],"commonly":[178],"used":[179],"models":[181],"previous":[183],"show":[188],"outperforms":[192],"all":[193],"baseline":[194],"models,":[195],"achieved":[197],"state-of-art":[199],"performance":[200],"80.0%":[202],"accuracy":[203],"0.881":[205],"AUC.":[206]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}