{"id":"https://openalex.org/W4388465831","doi":"https://doi.org/10.3233/idt-230320","title":"Severity prediction in COVID-19 patients using clinical markers and explainable artificial intelligence: A stacked ensemble machine learning approach","display_name":"Severity prediction in COVID-19 patients using clinical markers and explainable artificial intelligence: A stacked ensemble machine learning approach","publication_year":2023,"publication_date":"2023-11-07","ids":{"openalex":"https://openalex.org/W4388465831","doi":"https://doi.org/10.3233/idt-230320"},"language":"en","primary_location":{"id":"doi:10.3233/idt-230320","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230320","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-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/A5064101712","display_name":"Krishnaraj Chadaga","orcid":"https://orcid.org/0000-0002-9459-8423"},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Krishnaraj Chadaga","raw_affiliation_strings":["Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002001465","display_name":"Srikanth Prabhu","orcid":"https://orcid.org/0000-0002-3826-1084"},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Srikanth Prabhu","raw_affiliation_strings":["Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011702834","display_name":"Niranjana Sampathila","orcid":"https://orcid.org/0000-0002-3345-360X"},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Niranjana Sampathila","raw_affiliation_strings":["Department of Biomedical Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007922994","display_name":"Rajagopala Chadaga","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajagopala Chadaga","raw_affiliation_strings":["Department of Mechanical and Industrial Engineering Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Industrial Engineering Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002001465","https://openalex.org/A5011702834"],"corresponding_institution_ids":["https://openalex.org/I164861460"],"apc_list":null,"apc_paid":null,"fwci":0.9451,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76870502,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"17","issue":"4","first_page":"959","last_page":"982"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9980000257492065,"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":0.9904999732971191,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/intensive-care-unit","display_name":"Intensive care unit","score":0.6381495594978333},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6181737184524536},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5260969400405884},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5021429061889648},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.4915259778499603},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.4771784842014313},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4766315221786499},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47260552644729614},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.46806800365448},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.4328271448612213},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.4178137481212616},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.3789740800857544},{"id":"https://openalex.org/keywords/medical-emergency","display_name":"Medical emergency","score":0.37462782859802246},{"id":"https://openalex.org/keywords/intensive-care-medicine","display_name":"Intensive care medicine","score":0.3404528498649597},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.15369942784309387},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.11470142006874084}],"concepts":[{"id":"https://openalex.org/C2776376669","wikidata":"https://www.wikidata.org/wiki/Q5094647","display_name":"Intensive care unit","level":2,"score":0.6381495594978333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6181737184524536},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5260969400405884},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5021429061889648},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.4915259778499603},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.4771784842014313},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4766315221786499},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47260552644729614},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.46806800365448},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4328271448612213},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.4178137481212616},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.3789740800857544},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.37462782859802246},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.3404528498649597},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.15369942784309387},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.11470142006874084},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/idt-230320","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230320","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W2103672265","https://openalex.org/W2429796325","https://openalex.org/W2981731882","https://openalex.org/W3012054129","https://openalex.org/W3015433395","https://openalex.org/W3025394897","https://openalex.org/W3025504737","https://openalex.org/W3031876060","https://openalex.org/W3035399681","https://openalex.org/W3035941308","https://openalex.org/W3038018847","https://openalex.org/W3046994873","https://openalex.org/W3047268902","https://openalex.org/W3070886816","https://openalex.org/W3091281797","https://openalex.org/W3091829098","https://openalex.org/W3092284106","https://openalex.org/W3092436046","https://openalex.org/W3093068007","https://openalex.org/W3104769194","https://openalex.org/W3112971251","https://openalex.org/W3116070494","https://openalex.org/W3118270083","https://openalex.org/W3120105983","https://openalex.org/W3121555817","https://openalex.org/W3123695557","https://openalex.org/W3127076855","https://openalex.org/W3127469572","https://openalex.org/W3130958407","https://openalex.org/W3137264488","https://openalex.org/W3137313434","https://openalex.org/W3138595103","https://openalex.org/W3139161421","https://openalex.org/W3145918802","https://openalex.org/W3146264788","https://openalex.org/W3150135197","https://openalex.org/W3151561918","https://openalex.org/W3151773574","https://openalex.org/W3153859749","https://openalex.org/W3156360893","https://openalex.org/W3157270914","https://openalex.org/W3158893221","https://openalex.org/W3163967588","https://openalex.org/W3193291778","https://openalex.org/W3194015586","https://openalex.org/W3205738261","https://openalex.org/W4206009515","https://openalex.org/W4206950334","https://openalex.org/W4210659135","https://openalex.org/W4210936308","https://openalex.org/W4212976187","https://openalex.org/W4224273800","https://openalex.org/W4224981446","https://openalex.org/W4224986654","https://openalex.org/W4225912411","https://openalex.org/W4283643878","https://openalex.org/W4284885911","https://openalex.org/W4294559022","https://openalex.org/W4303449068","https://openalex.org/W4313453311","https://openalex.org/W4313830553","https://openalex.org/W4316813167","https://openalex.org/W4366768437","https://openalex.org/W4372311383","https://openalex.org/W4383998070","https://openalex.org/W4385606583"],"related_works":["https://openalex.org/W2165912799","https://openalex.org/W2735662278","https://openalex.org/W2382615723","https://openalex.org/W4311804456","https://openalex.org/W1987484445","https://openalex.org/W2623658258","https://openalex.org/W1969219540","https://openalex.org/W2143413548","https://openalex.org/W2370459448","https://openalex.org/W2105067402"],"abstract_inverted_index":{"The":[0,172],"recent":[1],"COVID-19":[2,127,135,184,244,248],"pandemic":[3],"had":[4],"wreaked":[5],"havoc":[6],"worldwide,":[7],"causing":[8],"a":[9,26,30,50,71],"massive":[10],"strain":[11],"on":[12,110,180,214],"already-struggling":[13],"healthcare":[14],"infrastructure.":[15],"Vaccines":[16],"have":[17,116],"been":[18],"rolled":[19],"out":[20],"and":[21,37,57,152,160,208,233,246],"seem":[22],"effective":[23],"in":[24],"preventing":[25],"bad":[27],"prognosis.":[28],"However,":[29],"small":[31],"part":[32],"of":[33,52,195],"the":[34,74,126,148,161,170,188,220,239],"population":[35],"(elderly":[36],"people":[38],"with":[39,67,99,192],"comorbidities)":[40],"continues":[41],"to":[42,44,49,62,146,203,242],"succumb":[43],"this":[45,93,97],"deadly":[46],"virus.":[47],"Due":[48],"lack":[51],"available":[53,88],"resources,":[54],"appropriate":[55],"triaging":[56],"treatment":[58],"planning":[59],"are":[60,86],"vital":[61],"improving":[63],"outcomes":[64],"for":[65,89,129,157,169],"patients":[66,245],"COVID-19.":[68],"Assessing":[69],"whether":[70,181],"patient":[72,112,185],"requires":[73],"hospital\u2019s":[75],"Intensive":[76],"Care":[77],"Unit":[78],"(ICU)":[79],"is":[80],"very":[81],"important":[82],"since":[83],"these":[84],"units":[85],"not":[87],"every":[90],"patient.":[91],"In":[92],"research,":[94],"we":[95],"automate":[96],"assessment":[98],"stacked":[100,174],"ensemble":[101],"machine":[102],"learning":[103],"models":[104],"that":[105,219],"predict":[106],"ICU":[107,189],"admission":[108],"based":[109],"general":[111],"laboratory":[113],"data.":[114],"We":[115],"built":[117],"an":[118,182,193],"explainable":[119],"decision":[120,178],"support":[121,179],"model":[122,175],"which":[123],"automatically":[124],"scores":[125],"severity":[128],"individual":[130],"patients.":[131],"Data":[132],"from":[133,139],"1925":[134],"positive":[136],"patients,":[137],"sourced":[138],"three":[140],"top-tier":[141],"Brazilian":[142],"hospitals,":[143],"were":[144,155,165,224],"used":[145,202],"design":[147],"model.":[149,171],"Pearson\u2019s":[150],"correlation":[151],"mutual":[153],"information":[154],"utilized":[156],"feature":[158],"selection,":[159],"top":[162],"24":[163],"features":[164],"chosen":[166],"as":[167],"input":[168],"final":[173],"could":[176],"provide":[177],"admitted":[183],"would":[186],"require":[187],"or":[190],"not,":[191],"accuracy":[194],"88%.":[196],"Explainable":[197],"Artificial":[198],"Intelligence":[199],"(EAI)":[200],"was":[201,217],"undertake":[204],"system-level":[205],"insight":[206],"discovery":[207],"investigate":[209],"various":[210],"clinical":[211],"variables\u2019":[212],"impact":[213],"decision-making.":[215],"It":[216],"found":[218],"most":[221],"critical":[222],"factors":[223],"respiratory":[225],"rate,":[226],"temperature,":[227],"blood":[228],"pressure,":[229],"lactate":[230],"dehydrogenase,":[231],"hemoglobin,":[232],"age.":[234],"Healthcare":[235],"facilities":[236],"can":[237],"use":[238],"proposed":[240],"approach":[241],"categorize":[243],"prevent":[247],"fatalities.":[249]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
