{"id":"https://openalex.org/W4214948442","doi":"https://doi.org/10.1109/icaiic54071.2022.9722659","title":"A Machine Learning Approach in Evaluating Symptom Screening in Predicting COVID-19","display_name":"A Machine Learning Approach in Evaluating Symptom Screening in Predicting COVID-19","publication_year":2022,"publication_date":"2022-02-21","ids":{"openalex":"https://openalex.org/W4214948442","doi":"https://doi.org/10.1109/icaiic54071.2022.9722659"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic54071.2022.9722659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic54071.2022.9722659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5032870088","display_name":"John Althom A. Mendoza","orcid":null},"institutions":[{"id":"https://openalex.org/I103911934","display_name":"University of the Philippines System","ror":"https://ror.org/02hqkr514","country_code":"PH","type":"education","lineage":["https://openalex.org/I103911934"]},{"id":"https://openalex.org/I5791819","display_name":"University of the Philippines Manila","ror":"https://ror.org/01rrczv41","country_code":"PH","type":"education","lineage":["https://openalex.org/I103911934","https://openalex.org/I5791819"]}],"countries":["PH"],"is_corresponding":true,"raw_author_name":"John Althom A. Mendoza","raw_affiliation_strings":["University of the Philippines,College of Engineering,Department of Computer Science,Philippines","Department of Computer Science, College of Engineering, University of the Philippines, Philippines"],"affiliations":[{"raw_affiliation_string":"University of the Philippines,College of Engineering,Department of Computer Science,Philippines","institution_ids":["https://openalex.org/I103911934","https://openalex.org/I5791819"]},{"raw_affiliation_string":"Department of Computer Science, College of Engineering, University of the Philippines, Philippines","institution_ids":["https://openalex.org/I103911934"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086938101","display_name":"Geoffrey A. Solano","orcid":"https://orcid.org/0000-0002-4223-1355"},"institutions":[{"id":"https://openalex.org/I5791819","display_name":"University of the Philippines Manila","ror":"https://ror.org/01rrczv41","country_code":"PH","type":"education","lineage":["https://openalex.org/I103911934","https://openalex.org/I5791819"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Geoffrey A. Solano","raw_affiliation_strings":["University of the Philippines,College of Arts and Sciences,Department of Physical Sciences and Mathematics,Manila,Philippines","Department of Physical Sciences and Mathematics, College of Arts and Sciences, University of the Philippines, Manila, Philippines"],"affiliations":[{"raw_affiliation_string":"University of the Philippines,College of Arts and Sciences,Department of Physical Sciences and Mathematics,Manila,Philippines","institution_ids":["https://openalex.org/I5791819"]},{"raw_affiliation_string":"Department of Physical Sciences and Mathematics, College of Arts and Sciences, University of the Philippines, Manila, Philippines","institution_ids":["https://openalex.org/I5791819"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086119076","display_name":"Marc Jermaine Pontiveros","orcid":"https://orcid.org/0000-0002-0986-6236"},"institutions":[{"id":"https://openalex.org/I103911934","display_name":"University of the Philippines System","ror":"https://ror.org/02hqkr514","country_code":"PH","type":"education","lineage":["https://openalex.org/I103911934"]},{"id":"https://openalex.org/I5791819","display_name":"University of the Philippines Manila","ror":"https://ror.org/01rrczv41","country_code":"PH","type":"education","lineage":["https://openalex.org/I103911934","https://openalex.org/I5791819"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Marc Jermaine Pontiveros","raw_affiliation_strings":["University of the Philippines,College of Engineering,Department of Computer Science,Philippines","Department of Physical Sciences and Mathematics, College of Arts and Sciences, University of the Philippines, Manila, Philippines","Department of Computer Science, College of Engineering, University of the Philippines, Philippines"],"affiliations":[{"raw_affiliation_string":"University of the Philippines,College of Engineering,Department of Computer Science,Philippines","institution_ids":["https://openalex.org/I103911934","https://openalex.org/I5791819"]},{"raw_affiliation_string":"Department of Physical Sciences and Mathematics, College of Arts and Sciences, University of the Philippines, Manila, Philippines","institution_ids":["https://openalex.org/I5791819"]},{"raw_affiliation_string":"Department of Computer Science, College of Engineering, University of the Philippines, Philippines","institution_ids":["https://openalex.org/I103911934"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031477201","display_name":"Jaime Dl","orcid":null},"institutions":[{"id":"https://openalex.org/I103911934","display_name":"University of the Philippines System","ror":"https://ror.org/02hqkr514","country_code":"PH","type":"education","lineage":["https://openalex.org/I103911934"]},{"id":"https://openalex.org/I5791819","display_name":"University of the Philippines Manila","ror":"https://ror.org/01rrczv41","country_code":"PH","type":"education","lineage":["https://openalex.org/I103911934","https://openalex.org/I5791819"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Jaime Dl Caro","raw_affiliation_strings":["University of the Philippines,College of Engineering,Department of Computer Science,Philippines","Department of Computer Science, College of Engineering, University of the Philippines, Philippines"],"affiliations":[{"raw_affiliation_string":"University of the Philippines,College of Engineering,Department of Computer Science,Philippines","institution_ids":["https://openalex.org/I103911934","https://openalex.org/I5791819"]},{"raw_affiliation_string":"Department of Computer Science, College of Engineering, University of the Philippines, Philippines","institution_ids":["https://openalex.org/I103911934"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011724604","display_name":"Peter Martin D. Gomez","orcid":null},"institutions":[{"id":"https://openalex.org/I3129360473","display_name":"University of Manila","ror":"https://ror.org/04c9af145","country_code":"PH","type":"education","lineage":["https://openalex.org/I3129360473"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Peter Martin D. Gomez","raw_affiliation_strings":["Dashlabs.ai,Manila,Philippines","Dashlabs.ai, Manila, Philippines"],"affiliations":[{"raw_affiliation_string":"Dashlabs.ai,Manila,Philippines","institution_ids":["https://openalex.org/I3129360473"]},{"raw_affiliation_string":"Dashlabs.ai, Manila, Philippines","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046232405","display_name":"Conner G. Manuel","orcid":null},"institutions":[{"id":"https://openalex.org/I3129360473","display_name":"University of Manila","ror":"https://ror.org/04c9af145","country_code":"PH","type":"education","lineage":["https://openalex.org/I3129360473"]},{"id":"https://openalex.org/I2802181614","display_name":"Philippine General Hospital","ror":"https://ror.org/00a56am39","country_code":"PH","type":"healthcare","lineage":["https://openalex.org/I103911934","https://openalex.org/I2802181614"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Conner G. Manuel","raw_affiliation_strings":["Dashlabs.ai,Manila,Philippines","Dashlabs.ai, Manila, Philippines","Philippine Red Cross, Manila, Philippines"],"affiliations":[{"raw_affiliation_string":"Dashlabs.ai,Manila,Philippines","institution_ids":["https://openalex.org/I3129360473"]},{"raw_affiliation_string":"Dashlabs.ai, Manila, Philippines","institution_ids":[]},{"raw_affiliation_string":"Philippine Red Cross, Manila, Philippines","institution_ids":["https://openalex.org/I2802181614"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017446499","display_name":"Paulyn Jean Buenaflor Rosell-Ubial","orcid":null},"institutions":[{"id":"https://openalex.org/I2802181614","display_name":"Philippine General Hospital","ror":"https://ror.org/00a56am39","country_code":"PH","type":"healthcare","lineage":["https://openalex.org/I103911934","https://openalex.org/I2802181614"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Paulyn Jean Buenaflor Rosell-Ubial","raw_affiliation_strings":["Philippine Red Cross,Manila,Philippines","Philippine Red Cross, Manila, Philippines"],"affiliations":[{"raw_affiliation_string":"Philippine Red Cross,Manila,Philippines","institution_ids":["https://openalex.org/I2802181614"]},{"raw_affiliation_string":"Philippine Red Cross, Manila, Philippines","institution_ids":["https://openalex.org/I2802181614"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083955728","display_name":"Michael Tee","orcid":"https://orcid.org/0000-0003-0113-8290"},"institutions":[{"id":"https://openalex.org/I5791819","display_name":"University of the Philippines Manila","ror":"https://ror.org/01rrczv41","country_code":"PH","type":"education","lineage":["https://openalex.org/I103911934","https://openalex.org/I5791819"]},{"id":"https://openalex.org/I2802181614","display_name":"Philippine General Hospital","ror":"https://ror.org/00a56am39","country_code":"PH","type":"healthcare","lineage":["https://openalex.org/I103911934","https://openalex.org/I2802181614"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Michael Tee","raw_affiliation_strings":["University of the Philippines,College of Medicine,Department of Physiology,Manila,Philippines","Philippine Red Cross, Manila, Philippines","Department of Physiology, College of Medicine, University of the Philippines, Manila, Philippines"],"affiliations":[{"raw_affiliation_string":"University of the Philippines,College of Medicine,Department of Physiology,Manila,Philippines","institution_ids":["https://openalex.org/I5791819"]},{"raw_affiliation_string":"Philippine Red Cross, Manila, Philippines","institution_ids":["https://openalex.org/I2802181614"]},{"raw_affiliation_string":"Department of Physiology, College of Medicine, University of the Philippines, Manila, Philippines","institution_ids":["https://openalex.org/I5791819"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5032870088"],"corresponding_institution_ids":["https://openalex.org/I103911934","https://openalex.org/I5791819"],"apc_list":null,"apc_paid":null,"fwci":0.2862,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52513916,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"188","last_page":"193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9909999966621399,"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/T11754","display_name":"SARS-CoV-2 detection and testing","score":0.9639999866485596,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"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/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6383309960365295},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6262835264205933},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6131659746170044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5958136320114136},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5713614225387573},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.530417263507843},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.49897098541259766},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4910721778869629},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.4907725751399994},{"id":"https://openalex.org/keywords/gold-standard","display_name":"Gold standard (test)","score":0.466541051864624},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4466651380062103},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.4379558861255646},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4240991473197937},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20671603083610535},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.17921075224876404},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.10137626528739929}],"concepts":[{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6383309960365295},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6262835264205933},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6131659746170044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5958136320114136},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5713614225387573},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.530417263507843},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.49897098541259766},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4910721778869629},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.4907725751399994},{"id":"https://openalex.org/C40993552","wikidata":"https://www.wikidata.org/wiki/Q514654","display_name":"Gold standard (test)","level":2,"score":0.466541051864624},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4466651380062103},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.4379558861255646},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4240991473197937},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20671603083610535},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.17921075224876404},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.10137626528739929},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic54071.2022.9722659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic54071.2022.9722659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W3001465255","https://openalex.org/W3011032288","https://openalex.org/W3015198978","https://openalex.org/W3015664205","https://openalex.org/W3022240561","https://openalex.org/W3031525229","https://openalex.org/W3032540099","https://openalex.org/W3033769823","https://openalex.org/W3041322293","https://openalex.org/W3046993329","https://openalex.org/W3119464161"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2011666252","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456"],"abstract_inverted_index":{"COVID-19":[0],"is":[1,82,84,147,293],"a":[2,38,51,63,99,169,252,295],"disease":[3,30],"caused":[4,94],"by":[5,86,109],"the":[6,32,79,90,95,131,177,181,193,219,226,247,270,283,313,322],"severe":[7],"acute":[8],"respiratory":[9,33],"syndrome":[10],"coronavirus":[11],"2":[12],"(SARS-CoV-2)":[13],"that,":[14],"to":[15,60,88,151,154,162,238,312],"date,":[16],"has":[17,104,254,304],"over":[18],"245":[19],"million":[20,27],"confirmed":[21],"cases":[22],"and":[23,35,48,111,135,211,225,264,324],"claimed":[24],"almost":[25],"5":[26],"lives.":[28],"This":[29,74],"attacks":[31],"system":[34,150],"comes":[36],"with":[37,282],"number":[39,64],"of":[40,53,65,71,76,123,133,171,176,269,315,326],"symptoms.":[41,54],"The":[42,120,256],"US":[43],"Center":[44],"for":[45,118,157,232,299],"Disease":[46],"Control":[47],"Prevention":[49],"presents":[50],"set":[52,170],"However,":[55],"these":[56],"symptoms":[57,77,102,172,234,274,278],"only":[58],"begin":[59],"manifest":[61],"after":[62],"days,":[66],"which":[67],"prevents":[68],"early":[69,80],"detection":[70],"this":[72,138],"disease.":[73],"absence":[75],"during":[78],"stages":[81],"what":[83],"considered":[85],"many":[87],"be":[89,152],"very":[91],"factor":[92],"that":[93,277,290],"virus":[96],"into":[97],"becoming":[98],"pandemic.":[100],"Nonetheless,":[101],"checking":[103,125],"been":[105],"used":[106],"in":[107,128,184],"practice":[108],"commercial":[110],"business":[112],"establishments":[113],"as":[114,237,318],"an":[115,148,302],"initial":[116],"screening":[117,146,292],"COVID-19.":[119,158,255,305],"bothersome":[121],"process":[122,298],"symptom":[124,145,291],"are":[126,173,199,235,243],"still":[127],"place":[129],"at":[130,321],"entrances":[132,323],"malls":[134],"airports.":[136],"In":[137,306],"study,":[139],"we":[140,288],"determine":[141,163],"whether":[142,164,239,249,301],"or":[143,165,168,240,250],"not":[144,166,241,251,280,294],"effective":[149,174],"employed":[153],"assess":[155],"individuals":[156],"Specifically,":[159],"it":[160,308],"aims":[161],"one":[167],"predictors":[175],"RT-PCR":[178,284],"test":[179],"results,":[180],"gold":[182],"standard":[183],"Covid-19":[185],"testing,":[186],"using":[187,201,218],"machine":[188],"learning.":[189],"Using":[190],"data":[191],"from":[192],"Philippine":[194],"Red":[195],"Cross,":[196],"classification":[197],"models":[198,215],"developed":[200],"LightGBM,":[202],"AdaBoost,":[203],"Gaussian":[204],"Na\u00efve-Bayes,":[205],"MultiLayer":[206],"Perceptron,":[207],"Quadratic":[208],"Discriminant":[209],"Analysis":[210],"Decision":[212],"Tree.":[213],"These":[214],"were":[216],"evaluated":[217],"following":[220],"metrics:":[221],"precision,":[222],"sensitivity,":[223],"specificity":[224],"type":[227,258],"II":[228,259],"error":[229,260],"rate.":[230],"Furthermore,":[231],"explainability,":[233],"analyzed":[236],"they":[242],"relatively":[244],"influential":[245],"on":[246],"predicting":[248],"patient":[253],"high":[257],"rate,":[261],"low":[262,265],"sensitivity":[263],"relative":[266],"predictor":[267,273],"scores":[268],"most":[271],"significant":[272],"clearly":[275],"show":[276],"do":[279],"correlate":[281],"testing":[285],"results.":[286],"Thus,":[287],"conclude":[289],"medically":[296],"suitable":[297],"determining":[300],"individual":[303],"fact,":[307],"even":[309],"exposes":[310],"us":[311],"risk":[314],"viral":[316],"transmission":[317],"people":[319],"congregate":[320],"lobbies":[325],"establishments.":[327]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-02-25T08:12:03.925757","created_date":"2025-10-10T00:00:00"}