{"id":"https://openalex.org/W4403211511","doi":"https://doi.org/10.1109/cibcb58642.2024.10702108","title":"Improving Machine Learning Based Sepsis Diagnosis Using Heart Rate Variability","display_name":"Improving Machine Learning Based Sepsis Diagnosis Using Heart Rate Variability","publication_year":2024,"publication_date":"2024-08-27","ids":{"openalex":"https://openalex.org/W4403211511","doi":"https://doi.org/10.1109/cibcb58642.2024.10702108"},"language":"en","primary_location":{"id":"doi:10.1109/cibcb58642.2024.10702108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb58642.2024.10702108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","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/A5108005975","display_name":"Sai A. Balaji","orcid":"https://orcid.org/0000-0002-6539-9660"},"institutions":[{"id":"https://openalex.org/I4210092015","display_name":"Opexa Therapeutics (United States)","ror":"https://ror.org/00gf55f61","country_code":"US","type":"company","lineage":["https://openalex.org/I4210092015"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sai Balaji","raw_affiliation_strings":["The Woodlands College Park High School,The Woodlands,TX,United States"],"affiliations":[{"raw_affiliation_string":"The Woodlands College Park High School,The Woodlands,TX,United States","institution_ids":["https://openalex.org/I4210092015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101926560","display_name":"Christopher Sun","orcid":"https://orcid.org/0000-0002-1906-6080"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Sun","raw_affiliation_strings":["Stanford University,Stanford,CA,United States"],"affiliations":[{"raw_affiliation_string":"Stanford University,Stanford,CA,United States","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086448230","display_name":"Anaiy Somalwar","orcid":"https://orcid.org/0000-0003-4280-1642"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anaiy Somalwar","raw_affiliation_strings":["University of California, Berkeley,Berkeley,CA,United States"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley,Berkeley,CA,United States","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5108005975"],"corresponding_institution_ids":["https://openalex.org/I4210092015"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15954062,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9768999814987183,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9768999814987183,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9261000156402588,"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":0.667899489402771},{"id":"https://openalex.org/keywords/sepsis","display_name":"Sepsis","score":0.4858967661857605},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4430527687072754},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4274609088897705},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17154839634895325},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.15198883414268494}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.667899489402771},{"id":"https://openalex.org/C2778384902","wikidata":"https://www.wikidata.org/wiki/Q183134","display_name":"Sepsis","level":2,"score":0.4858967661857605},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4430527687072754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4274609088897705},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17154839634895325},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.15198883414268494}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cibcb58642.2024.10702108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb58642.2024.10702108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","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":14,"referenced_works":["https://openalex.org/W1700449338","https://openalex.org/W1943063538","https://openalex.org/W2516809705","https://openalex.org/W2748885884","https://openalex.org/W2891765533","https://openalex.org/W2944988359","https://openalex.org/W2998524378","https://openalex.org/W2998853022","https://openalex.org/W3015460073","https://openalex.org/W3016555942","https://openalex.org/W3020776760","https://openalex.org/W3083289130","https://openalex.org/W4362522808","https://openalex.org/W4386307515"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"The":[0,107],"early":[1],"and":[2,44,51,74,77,102,137],"accurate":[3],"diagnosis":[4,154],"of":[5,72,96,100,105,149,160],"sepsis":[6,30,153],"is":[7,86,112],"critical":[8],"for":[9,29,139],"enhancing":[10],"patient":[11],"outcomes.":[12],"This":[13,142],"study":[14,143],"aims":[15],"to":[16,23,67,114,129],"use":[17],"heart":[18],"rate":[19],"variability":[20],"(HRV)":[21],"features":[22,34],"develop":[24],"an":[25,93,119],"effective":[26],"predictive":[27],"model":[28,79,85,111],"detection.":[31],"Critical":[32],"HRV":[33,90,150],"are":[35,55,65,127],"identified":[36],"through":[37,118],"feature":[38],"engineering":[39],"methods,":[40],"including":[41],"statistical":[42],"bootstrapping":[43],"the":[45,69,89,147,158],"Boruta":[46],"algorithm,":[47],"after":[48],"which":[49],"XGBoost":[50],"Random":[52],"Forest":[53],"classifiers":[54,76],"trained":[56,87],"with":[57],"differential":[58],"hyperparameter":[59],"settings.":[60],"In":[61],"addition,":[62],"ensemble":[63],"models":[64],"constructed":[66],"pool":[68],"prediction":[70],"probabilities":[71],"high-recall":[73],"high-precision":[75],"improve":[78],"performance.":[80],"Finally,":[81],"a":[82,98,103],"neural":[83,116],"network":[84,117],"on":[88,134],"features,":[91],"achieving":[92],"F1":[94],"score":[95],"0.805,":[97],"precision":[99],"0.851,":[101],"recall":[104],"0.763.":[106],"best-performing":[108],"machine":[109],"learning":[110],"compared":[113],"this":[115],"interpretability":[120],"analysis,":[121],"where":[122],"Local":[123],"Interpretable":[124],"Model-agnostic":[125],"Explanations":[126],"implemented":[128],"determine":[130],"decision-making":[131],"criterion":[132],"based":[133],"numerical":[135],"ranges":[136],"thresholds":[138],"specific":[140],"features.":[141],"not":[144],"only":[145],"highlights":[146],"efficacy":[148],"in":[151],"automated":[152],"but":[155],"also":[156],"increases":[157],"transparency":[159],"black":[161],"box":[162],"outputs,":[163],"maximizing":[164],"clinical":[165],"applicability.":[166]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
