{"id":"https://openalex.org/W4413412249","doi":"https://doi.org/10.1007/s44163-025-00305-w","title":"Predicting neonatal mortality using ensemble machine learning algorithms in the case of Ethiopian Rural Areas","display_name":"Predicting neonatal mortality using ensemble machine learning algorithms in the case of Ethiopian Rural Areas","publication_year":2025,"publication_date":"2025-08-22","ids":{"openalex":"https://openalex.org/W4413412249","doi":"https://doi.org/10.1007/s44163-025-00305-w"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00305-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00305-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00305-w.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00305-w.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115000460","display_name":"Melaku Alelign Mengstie","orcid":null},"institutions":[{"id":"https://openalex.org/I8764889","display_name":"University of Gondar","ror":"https://ror.org/0595gz585","country_code":"ET","type":"education","lineage":["https://openalex.org/I8764889"]}],"countries":["ET"],"is_corresponding":true,"raw_author_name":"Melaku Alelign Mengstie","raw_affiliation_strings":["Department of Information Science, College of Informatics, University of Gondar, Gondar, Ethiopia"],"affiliations":[{"raw_affiliation_string":"Department of Information Science, College of Informatics, University of Gondar, Gondar, Ethiopia","institution_ids":["https://openalex.org/I8764889"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5119381537","display_name":"Misganaw Telake Telele","orcid":null},"institutions":[{"id":"https://openalex.org/I8764889","display_name":"University of Gondar","ror":"https://ror.org/0595gz585","country_code":"ET","type":"education","lineage":["https://openalex.org/I8764889"]}],"countries":["ET"],"is_corresponding":false,"raw_author_name":"Misganaw Telake Telele","raw_affiliation_strings":["Department of Information Science, College of Informatics, University of Gondar, Gondar, Ethiopia"],"affiliations":[{"raw_affiliation_string":"Department of Information Science, College of Informatics, University of Gondar, Gondar, Ethiopia","institution_ids":["https://openalex.org/I8764889"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5115000460"],"corresponding_institution_ids":["https://openalex.org/I8764889"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":3.6803,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.9273569,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"5","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":0.9922999739646912,"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":0.9922999739646912,"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/T10596","display_name":"Child Nutrition and Water Access","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/2916","display_name":"Nutrition and Dietetics"},"field":{"id":"https://openalex.org/fields/29","display_name":"Nursing"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13410","display_name":"Immune responses and vaccinations","score":0.9269999861717224,"subfield":{"id":"https://openalex.org/subfields/2403","display_name":"Immunology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6323533058166504},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5316131114959717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4745638966560364},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4732264280319214},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3889980912208557}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6323533058166504},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5316131114959717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4745638966560364},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4732264280319214},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3889980912208557}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-025-00305-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00305-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00305-w.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:315de4b3e56c4c8fb4053feb138c00ea","is_oa":true,"landing_page_url":"https://doaj.org/article/315de4b3e56c4c8fb4053feb138c00ea","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-18 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00305-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00305-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00305-w.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413412249.pdf","grobid_xml":"https://content.openalex.org/works/W4413412249.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1991181258","https://openalex.org/W2053481403","https://openalex.org/W2103647733","https://openalex.org/W2791315675","https://openalex.org/W2895583801","https://openalex.org/W2966364722","https://openalex.org/W2972863974","https://openalex.org/W2981832810","https://openalex.org/W2982391067","https://openalex.org/W3002417451","https://openalex.org/W3087412377","https://openalex.org/W3119608572","https://openalex.org/W3149839747","https://openalex.org/W3156179678","https://openalex.org/W3183837412","https://openalex.org/W4236070523","https://openalex.org/W4296079469","https://openalex.org/W4297347562","https://openalex.org/W4311529522","https://openalex.org/W4316669506","https://openalex.org/W4321606917","https://openalex.org/W4366828815","https://openalex.org/W4377095901","https://openalex.org/W4383959668","https://openalex.org/W4384914918","https://openalex.org/W4386566925","https://openalex.org/W4386737856","https://openalex.org/W4391443701","https://openalex.org/W4401582220","https://openalex.org/W4405453421","https://openalex.org/W4405822398"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Abstract":[0],"Background":[1],"Each":[2],"year,":[3],"approximately":[4],"2.5":[5],"million":[6],"newborns":[7],"die":[8],"globally,":[9],"with":[10,27,171,271],"developing":[11],"countries":[12],"bearing":[13],"the":[14,22,69,94,98,124,127,158,162,168,188,201,207,260,272],"impact":[15,233],"of":[16,191,203,262],"this":[17],"crisis.":[18],"Sub-Saharan":[19],"Africa":[20],"has":[21],"highest":[23,169],"neonatal":[24,60,235,246,276],"mortality":[25,38,61,247,277],"rate,":[26],"Ethiopia":[28,64],"facing":[29],"alarmingly":[30],"high":[31],"figures,":[32],"particularly":[33],"in":[34,62,206,248],"rural":[35,63,249],"areas":[36],"where":[37],"is":[39],"significantly":[40],"higher":[41],"due":[42],"to":[43,54,88,122,133,230,274],"poor":[44],"healthcare":[45,264],"access":[46],"and":[47,72,81,92,118,136,138,153,181,212,268,282],"socio-economic":[48],"challenges.":[49],"Methods":[50],"This":[51,238],"study":[52,239],"aimed":[53],"develop":[55],"a":[56],"predictive":[57,243],"model":[58,244,258],"for":[59,139,245,254],"using":[65,97],"secondary":[66],"data":[67],"from":[68,220],"Ethiopian":[70],"Demographic":[71],"Health":[73],"Surveys":[74],"(2000\u20132019).":[75],"The":[76,257],"dataset":[77],"included":[78],"29,048":[79],"instances":[80],"22":[82],"relevant":[83],"features,":[84],"which":[85],"were":[86,120,224],"preprocessed":[87],"handle":[89],"missing":[90],"values":[91],"balance":[93],"class":[95],"distribution":[96],"Synthetic":[99],"Minority":[100],"oversampling":[101],"technique.":[102],"Several":[103],"ensemble":[104],"machine-learning":[105],"algorithms,":[106],"including":[107],"Random":[108],"Forest,":[109],"Gradient":[110,113,116],"Boosting,":[111,114,117],"Extreme":[112],"Light":[115],"CatBoost,":[119],"applied":[121],"build":[123],"model.":[125],"Additionally,":[126],"logistic":[128],"regression":[129],"algorithm":[130],"was":[131,144],"employed":[132],"enhance":[134],"transparency":[135],"interpretability":[137],"comparative":[140],"analysis.":[141],"Model":[142],"performance":[143,170],"evaluated":[145],"based":[146],"on":[147,226,234],"accuracy,":[148,173],"precision,":[149,175],"recall,":[150,177],"F1":[151,179],"score,":[152,180],"Receiver":[154,184],"Operating":[155,185],"Characteristic\u2014Area":[156,186],"Under":[157,187],"Curve.":[159],"Results":[160],"Among":[161],"algorithms":[163],"tested,":[164],"categorical":[165],"boosting":[166],"achieved":[167],"97.5%":[172,176,178],"97.52%":[174],"an":[182,241],"exceptional":[183],"Curve":[189],"value":[190],"99.57%.":[192],"Key":[193],"risk":[194],"factors":[195],"identified":[196],"include":[197],"BCG":[198],"vaccination":[199],"status,":[200],"number":[202],"under-five":[204],"children":[205],"household,":[208],"recent":[209],"diarrhea":[210],"episodes,":[211],"iron":[213],"tablet":[214],"intake":[215],"during":[216],"pregnancy.":[217],"Valuable":[218],"feedbacks":[219],"community":[221],"health":[222,280],"workers":[223],"provided":[225],"these":[227],"factors,":[228],"helping":[229],"refine":[231],"their":[232],"mortality.":[236],"Conclusions":[237],"developed":[240],"effective":[242],"Ethiopia,":[250],"providing":[251],"actionable":[252],"insights":[253],"targeted":[255],"interventions.":[256],"underscores":[259],"importance":[261],"improving":[263],"access,":[265],"maternal":[266],"health,":[267],"policy":[269],"reforms,":[270],"potential":[273],"reduce":[275],"through":[278],"mobile":[279],"apps":[281],"policymaker":[283],"collaboration.":[284]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
