{"id":"https://openalex.org/W4322744035","doi":"https://doi.org/10.1080/08839514.2022.2158273","title":"Analysis of Birth Data using Ensemble Modeling Techniques","display_name":"Analysis of Birth Data using Ensemble Modeling Techniques","publication_year":2023,"publication_date":"2023-02-28","ids":{"openalex":"https://openalex.org/W4322744035","doi":"https://doi.org/10.1080/08839514.2022.2158273"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2022.2158273","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2158273","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2158273?download=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2158273?download=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079409706","display_name":"Sohaib Latif","orcid":"https://orcid.org/0000-0002-0690-2326"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sohaib Latif","raw_affiliation_strings":["School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, Anhui, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, Anhui, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067992545","display_name":"Xianwen Fang","orcid":"https://orcid.org/0000-0001-8531-7215"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xian Wen Fang","raw_affiliation_strings":["School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, Anhui, China"],"raw_orcid":"https://orcid.org/0000-0001-8531-7215","affiliations":[{"raw_affiliation_string":"School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, Anhui, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011213868","display_name":"Kaleem Arshid","orcid":"https://orcid.org/0000-0001-9071-360X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaleem Arshid","raw_affiliation_strings":["Beijing Key Laboratory of Trusted Computing, Faculty of Information Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Trusted Computing, Faculty of Information Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006566886","display_name":"Abdullah Almuhaimeed","orcid":"https://orcid.org/0000-0002-1155-9382"},"institutions":[{"id":"https://openalex.org/I1284598098","display_name":"King Abdulaziz City for Science and Technology","ror":"https://ror.org/05tdz6m39","country_code":"SA","type":"facility","lineage":["https://openalex.org/I1284598098"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Abdullah Almuhaimeed","raw_affiliation_strings":["Digital Health Institute, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Digital Health Institute, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I1284598098"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078863502","display_name":"Azhar Imran","orcid":"https://orcid.org/0000-0003-3598-2780"},"institutions":[{"id":"https://openalex.org/I899713450","display_name":"Air University","ror":"https://ror.org/03yfe9v83","country_code":"PK","type":"education","lineage":["https://openalex.org/I899713450"]}],"countries":["PK"],"is_corresponding":true,"raw_author_name":"Azhar Imran","raw_affiliation_strings":["Faculty of Computing and Artificial Intelligence, Air University, Islamabad, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computing and Artificial Intelligence, Air University, Islamabad, Pakistan","institution_ids":["https://openalex.org/I899713450"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070324443","display_name":"Mansoor Alghamdi","orcid":"https://orcid.org/0000-0002-2891-6374"},"institutions":[{"id":"https://openalex.org/I72264486","display_name":"University of Tabuk","ror":"https://ror.org/04yej8x59","country_code":"SA","type":"education","lineage":["https://openalex.org/I72264486"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mansoor Alghamdi","raw_affiliation_strings":["Department of Computer Science, Applied College, University of Tabuk, Tabuk, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Applied College, University of Tabuk, Tabuk, Saudi Arabia","institution_ids":["https://openalex.org/I72264486"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5078863502"],"corresponding_institution_ids":["https://openalex.org/I899713450"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":3.7039,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.92455859,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"37","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10209","display_name":"Global Maternal and Child Health","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T10209","display_name":"Global Maternal and Child Health","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.947700023651123,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10453","display_name":"Maternal and Perinatal Health Interventions","score":0.9146000146865845,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"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/random-forest","display_name":"Random forest","score":0.8123779296875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7920653820037842},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7716602087020874},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7671321630477905},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7196172475814819},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6875597238540649},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.64580237865448},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6441960334777832},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6118124127388},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.552971363067627},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.550428032875061},{"id":"https://openalex.org/keywords/quadratic-classifier","display_name":"Quadratic classifier","score":0.5000319480895996},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.48389992117881775},{"id":"https://openalex.org/keywords/margin-classifier","display_name":"Margin classifier","score":0.4540281593799591},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.4289305806159973},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33416831493377686}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.8123779296875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7920653820037842},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7716602087020874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7671321630477905},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7196172475814819},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6875597238540649},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.64580237865448},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6441960334777832},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6118124127388},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.552971363067627},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.550428032875061},{"id":"https://openalex.org/C52620605","wikidata":"https://www.wikidata.org/wiki/Q7268357","display_name":"Quadratic classifier","level":3,"score":0.5000319480895996},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.48389992117881775},{"id":"https://openalex.org/C173102733","wikidata":"https://www.wikidata.org/wiki/Q6760396","display_name":"Margin classifier","level":3,"score":0.4540281593799591},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.4289305806159973},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33416831493377686},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2022.2158273","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2158273","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2158273?download=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:97d78c4542594078b8644f7f19ec73be","is_oa":true,"landing_page_url":"https://doaj.org/article/97d78c4542594078b8644f7f19ec73be","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 37, Iss 1 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2022.2158273","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2158273","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2158273?download=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4322744035.pdf","grobid_xml":"https://content.openalex.org/works/W4322744035.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1759801498","https://openalex.org/W2016710902","https://openalex.org/W2068970508","https://openalex.org/W2092454808","https://openalex.org/W2101771006","https://openalex.org/W2188856651","https://openalex.org/W2331970566","https://openalex.org/W2487770199","https://openalex.org/W2769614055","https://openalex.org/W2774072613","https://openalex.org/W2899636063","https://openalex.org/W3033376681","https://openalex.org/W3047114049","https://openalex.org/W4244207479"],"related_works":["https://openalex.org/W1845209238","https://openalex.org/W2125266525","https://openalex.org/W2888937984","https://openalex.org/W2273564766","https://openalex.org/W2407804800","https://openalex.org/W1568704199","https://openalex.org/W108062576","https://openalex.org/W2128012032","https://openalex.org/W2149131139","https://openalex.org/W2896010623"],"abstract_inverted_index":{"Machine":[0,54],"learning":[1,37,55,71,80,132,250,259],"and":[2,18,38,48,100,158,201,232,264],"data":[3,12,39,47,92],"mining":[4,40],"are":[5],"being":[6],"used":[7,76,114,164],"in":[8,20,61,69,299,303],"different":[9,301],"fields":[10,302],"like":[11],"analysis,":[13],"prediction,":[14],"image":[15],"processing,":[16],"etc.,":[17],"particularly":[19],"healthcare.":[21],"Over":[22],"the":[23,52,121,124,136,141,145,175,178,187,206,210,220,248,255,285,294,304],"past":[24],"decade,":[25],"several":[26],"types":[27],"of":[28,78,123,144,177,190,212,257,269],"research":[29,68,298],"have":[30,75,184,229],"been":[31],"carried":[32],"out":[33],"focusing":[34],"on":[35],"machine":[36,70,79,131,193,249,258],"application":[41],"to":[42,66,81,93,104,134,279,283],"generate":[43],"intuitions":[44],"from":[45,140],"historical":[46,91],"make":[49,97,107],"predictions":[50,99],"about":[51],"results.":[53],"algorithms":[56,77,133,260],"play":[57],"a":[58,170,271],"vital":[59],"role":[60],"improving":[62],"healthcare":[63],"systems":[64,83],"due":[65],"continuous":[67],"applications.":[72],"Several":[73],"researchers":[74],"develop":[82],"for":[84,120,168,174,296],"decision":[85],"support,":[86],"analyze":[87],"clinical":[88],"aspects,":[89],"use":[90],"extract":[94],"useful":[95],"information,":[96],"future":[98],"categorize":[101],"diseases,":[102],"etc.":[103],"help":[105,276],"physicians":[106],"better":[108],"decisions.":[109],"In":[110],"this":[111],"study,":[112],"we":[113],"an":[115],"ensemble":[116,172,242],"modeling":[117,243],"voting":[118,171,188],"technique":[119],"classification":[122,176,265],"birth":[125,179],"dataset.":[126,180],"Ensemble":[127,252],"models":[128,253],"combine":[129],"individual":[130],"improve":[135,284],"accuracy":[137,231,239,256],"by":[138,241,261],"predicting":[139],"combined":[142],"output":[143],"base":[146,166],"classifiers.":[147],"Gradient":[148],"boosting":[149,215],"classifier":[150,156,161,189,203,216,228,234],"(GBC),":[151],"random":[152,195,221],"forest":[153,196,222],"(RF),":[154,197],"bagging":[155,202,233],"(BC),":[157],"extra":[159,198,226],"trees":[160,199,227],"(ETC)":[162],"were":[163],"as":[165],"learners":[167],"making":[169],"model":[173],"The":[181,238,267],"results":[182,208],"produced":[183],"shown":[185],"that":[186],"support":[191],"vector":[192],"(SVM),":[194],"classifier,":[200],"has":[204,217,223,235],"given":[205],"best":[207],"with":[209],"proportion":[211],"94.78%,":[213],"gradient":[214],"84.39%":[218],"accuracy,":[219,225],"94.26%":[224],"94.02%":[230],"93.65%":[236],"accuracy.":[237],"achieved":[240],"is":[244],"far":[245],"higher":[246],"than":[247],"algorithms.":[251],"increase":[254],"reducing":[262],"variance":[263],"errors.":[266],"development":[268],"such":[270],"system":[272],"will":[273,291],"not":[274],"only":[275],"health":[277,287],"organizations":[278],"take":[280],"effective":[281],"measures":[282],"maternal":[286],"assessment":[288],"process":[289],"but":[290],"also":[292],"open":[293],"doors":[295],"interdisciplinary":[297],"two":[300],"region.":[305]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-12T06:13:28.667946","created_date":"2025-10-10T00:00:00"}
