{"id":"https://openalex.org/W4313452768","doi":"https://doi.org/10.1109/bibm55620.2022.9995429","title":"Machine Learning Algorithm to Predict Cardiac Output Using Arterial Pressure Waveform Analysis","display_name":"Machine Learning Algorithm to Predict Cardiac Output Using Arterial Pressure Waveform Analysis","publication_year":2022,"publication_date":"2022-12-06","ids":{"openalex":"https://openalex.org/W4313452768","doi":"https://doi.org/10.1109/bibm55620.2022.9995429"},"language":"en","primary_location":{"id":"doi:10.1109/bibm55620.2022.9995429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm55620.2022.9995429","pdf_url":null,"source":{"id":"https://openalex.org/S4363607730","display_name":"2022 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":"2022 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/A5102135163","display_name":"Ke Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I24193003","display_name":"Ricoh (Japan)","ror":"https://ror.org/02h4myp42","country_code":"JP","type":"company","lineage":["https://openalex.org/I24193003"]},{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Liao Ke","raw_affiliation_strings":["Japan Advanced Institute of Science and Technology,Ricoh Software Research Center (Beijing) Co., Ltd.,School of Information Science,Nomi,Ishikawa,Japan","School of Information Science, Ricoh Software Research Center (Beijing) Co., Ltd., Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan"],"affiliations":[{"raw_affiliation_string":"Japan Advanced Institute of Science and Technology,Ricoh Software Research Center (Beijing) Co., Ltd.,School of Information Science,Nomi,Ishikawa,Japan","institution_ids":["https://openalex.org/I24193003","https://openalex.org/I177738480"]},{"raw_affiliation_string":"School of Information Science, Ricoh Software Research Center (Beijing) Co., Ltd., Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan","institution_ids":["https://openalex.org/I24193003","https://openalex.org/I177738480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004592091","display_name":"Arma\u011fan Elibol","orcid":"https://orcid.org/0000-0003-0661-9536"},"institutions":[{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Armagan Elibol","raw_affiliation_strings":["Japan Advanced Institute of Science and Technology,School of Information Science,Nomi,Ishikawa,Japan","School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan"],"affiliations":[{"raw_affiliation_string":"Japan Advanced Institute of Science and Technology,School of Information Science,Nomi,Ishikawa,Japan","institution_ids":["https://openalex.org/I177738480"]},{"raw_affiliation_string":"School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan","institution_ids":["https://openalex.org/I177738480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100446384","display_name":"Wei Xiao","orcid":"https://orcid.org/0000-0001-9224-6726"},"institutions":[{"id":"https://openalex.org/I183519381","display_name":"Capital Medical University","ror":"https://ror.org/013xs5b60","country_code":"CN","type":"education","lineage":["https://openalex.org/I183519381"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wei","raw_affiliation_strings":["Capital Medical University,Xuanwu Hospital,Beijing,China","Xuanwu Hospital, Capital Medical University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Capital Medical University,Xuanwu Hospital,Beijing,China","institution_ids":["https://openalex.org/I183519381"]},{"raw_affiliation_string":"Xuanwu Hospital, Capital Medical University, Beijing, China","institution_ids":["https://openalex.org/I183519381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075024558","display_name":"Liao Cenyu","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liao Cenyu","raw_affiliation_strings":["Beijing Normal University,School of Mathematical Science,Beijing,China","School of Mathematical Science, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University,School of Mathematical Science,Beijing,China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"School of Mathematical Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100392222","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0003-2262-2508"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang Wei","raw_affiliation_strings":["Ricoh Software Research Center (Beijing) Co., Ltd.,Beijing,China","Ricoh Software Research Center (Beijing) Co., Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ricoh Software Research Center (Beijing) Co., Ltd.,Beijing,China","institution_ids":[]},{"raw_affiliation_string":"Ricoh Software Research Center (Beijing) Co., Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000452220","display_name":"Nak Young Chong","orcid":"https://orcid.org/0000-0001-5736-0769"},"institutions":[{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nak Young Chong","raw_affiliation_strings":["Japan Advanced Institute of Science and Technology,School of Information Science,Nomi,Ishikawa,Japan","School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan"],"affiliations":[{"raw_affiliation_string":"Japan Advanced Institute of Science and Technology,School of Information Science,Nomi,Ishikawa,Japan","institution_ids":["https://openalex.org/I177738480"]},{"raw_affiliation_string":"School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan","institution_ids":["https://openalex.org/I177738480"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5102135163"],"corresponding_institution_ids":["https://openalex.org/I177738480","https://openalex.org/I24193003"],"apc_list":null,"apc_paid":null,"fwci":10.2038,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.99,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1586","last_page":"1591"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11700","display_name":"Hemodynamic Monitoring and Therapy","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T11700","display_name":"Hemodynamic Monitoring and Therapy","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T10924","display_name":"Cardiovascular Health and Disease Prevention","score":0.9977999925613403,"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"}},{"id":"https://openalex.org/T10144","display_name":"Blood Pressure and Hypertension Studies","score":0.996999979019165,"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/waveform","display_name":"Waveform","score":0.6647086143493652},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5580141544342041},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5112659931182861},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4985344409942627},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49766090512275696},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44693148136138916},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.4326948821544647},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.325834721326828},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.26058825850486755},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.24826517701148987}],"concepts":[{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.6647086143493652},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5580141544342041},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5112659931182861},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4985344409942627},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49766090512275696},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44693148136138916},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.4326948821544647},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.325834721326828},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.26058825850486755},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.24826517701148987},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bibm55620.2022.9995429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm55620.2022.9995429","pdf_url":null,"source":{"id":"https://openalex.org/S4363607730","display_name":"2022 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":"2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.jaist.ac.jp:10119/18162","is_oa":false,"landing_page_url":"http://hdl.handle.net/10119/18162","pdf_url":null,"source":{"id":"https://openalex.org/S4406922663","display_name":"JAIST Repository","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W47993869","https://openalex.org/W621251951","https://openalex.org/W1487104887","https://openalex.org/W1531418665","https://openalex.org/W1946766441","https://openalex.org/W1969859651","https://openalex.org/W2018991752","https://openalex.org/W2019776257","https://openalex.org/W2024377214","https://openalex.org/W2046582107","https://openalex.org/W2046788142","https://openalex.org/W2067090053","https://openalex.org/W2071209977","https://openalex.org/W2078653663","https://openalex.org/W2107132985","https://openalex.org/W2112909794","https://openalex.org/W2122966699","https://openalex.org/W2157412697","https://openalex.org/W2166825834","https://openalex.org/W2185029892","https://openalex.org/W2808701318","https://openalex.org/W2916407632","https://openalex.org/W2972518285","https://openalex.org/W3114591112","https://openalex.org/W3150593963","https://openalex.org/W3185636491"],"related_works":["https://openalex.org/W1974895211","https://openalex.org/W2176409448","https://openalex.org/W2129841057","https://openalex.org/W3040712279","https://openalex.org/W2364769705","https://openalex.org/W2056136368","https://openalex.org/W2374664672","https://openalex.org/W4367555392","https://openalex.org/W2538520412","https://openalex.org/W2883092465"],"abstract_inverted_index":{"Cardiac":[0],"Output":[1],"(CO)":[2],"is":[3],"a":[4,13],"key":[5],"hemodynamic":[6],"variable":[7],"that":[8,126],"can":[9],"be":[10],"estimated":[11],"in":[12],"minimally":[14],"invasive":[15],"way":[16],"via":[17],"using":[18,96],"Arterial":[19,53],"Pressure":[20,54],"Waveform":[21,55],"Analysis":[22],"(APWA).":[23],"Many":[24],"models":[25,60,95,110],"use":[26],"circulation":[27],"mechanics":[28],"to":[29,43,50,61,149],"build":[30],"the":[31,52,63,67,73,88,97,103,112,127,132,156,175],"relationship":[32],"between":[33],"arterial":[34],"pressure":[35],"and":[36,47,57,72,76],"CO.":[37,64],"In":[38],"this":[39],"study,":[40],"we":[41],"attempt":[42],"apply":[44],"machine":[45,93],"learning":[46,94],"feature":[48,84],"engineering":[49],"analyze":[51],"(APW)":[56],"create":[58],"regression":[59],"predict":[62],"We":[65,86,101],"utilize":[66],"traditional":[68],"APWA":[69],"model":[70,130,158],"knowledge":[71],"time-domain,":[74],"frequency-domain,":[75],"other":[77],"characteristics":[78],"of":[79,145,171],"time":[80],"series":[81],"data":[82],"for":[83,91],"engineering.":[85],"present":[87],"benchmarking":[89],"results":[90,124],"several":[92],"MIMICII":[98],"waveform":[99],"database.":[100],"compare":[102],"predicted":[104],"CO":[105],"values":[106],"from":[107],"our":[108],"proposed":[109],"with":[111,163],"\u201cgold":[113],"standard\u201d":[114],"TCO":[115,164],"(CO":[116],"measured":[117],"by":[118],"intermittent":[119],"pulmonary":[120],"artery":[121],"thermodilution).":[122],"Our":[123],"show":[125],"Random":[128],"forest":[129],"has":[131],"most":[133],"accurate":[134],"agreement":[135],"(MSE:":[136],"1.421":[137],"$\\displaystyle":[138],"\\text{L}/\\min$,":[139,142,151],"bias:":[140,166],"$-0.01\\displaystyle":[141],"95%":[143,168],"limits":[144,170],"agreement:":[146,172],"$-2.35\\displaystyle":[147],"\\text{L}/\\min$":[148],"$+2.32\\displaystyle":[150],"percentage":[152],"error:":[153],"39.44%).":[154],"Notably,":[155],"XGBoost":[157],"demonstrates":[159],"good":[160],"tracking":[161],"ability":[162],"(radius":[165],"11.79o,":[167],"radius":[169],"\u00b128.89\u00b0),":[173],"achieving":[174],"clinically":[176],"acceptable":[177],"level.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
