{"id":"https://openalex.org/W3117934265","doi":"https://doi.org/10.1109/tencon50793.2020.9293890","title":"Machine Learning Analysis for Remote Prenatal Care","display_name":"Machine Learning Analysis for Remote Prenatal Care","publication_year":2020,"publication_date":"2020-11-16","ids":{"openalex":"https://openalex.org/W3117934265","doi":"https://doi.org/10.1109/tencon50793.2020.9293890","mag":"3117934265"},"language":"en","primary_location":{"id":"doi:10.1109/tencon50793.2020.9293890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon50793.2020.9293890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","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/A5030377440","display_name":"John Bautista","orcid":null},"institutions":[{"id":"https://openalex.org/I19722","display_name":"Ateneo de Manila University","ror":"https://ror.org/053kevk63","country_code":"PH","type":"education","lineage":["https://openalex.org/I19722"]}],"countries":["PH"],"is_corresponding":true,"raw_author_name":"John Mark Bautista","raw_affiliation_strings":["Department of Electronics, Computer, and Communications Engineering, Ateneo De Manila University, Quezon City, Philippines"],"affiliations":[{"raw_affiliation_string":"Department of Electronics, Computer, and Communications Engineering, Ateneo De Manila University, Quezon City, Philippines","institution_ids":["https://openalex.org/I19722"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047068030","display_name":"Quiel Andrew I. Quiwa","orcid":null},"institutions":[{"id":"https://openalex.org/I19722","display_name":"Ateneo de Manila University","ror":"https://ror.org/053kevk63","country_code":"PH","type":"education","lineage":["https://openalex.org/I19722"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Quiel Andrew I. Quiwa","raw_affiliation_strings":["Department of Electronics, Computer, and Communications Engineering, Ateneo De Manila University, Quezon City, Philippines"],"affiliations":[{"raw_affiliation_string":"Department of Electronics, Computer, and Communications Engineering, Ateneo De Manila University, Quezon City, Philippines","institution_ids":["https://openalex.org/I19722"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046540816","display_name":"Rosula Reyes","orcid":"https://orcid.org/0000-0002-8160-7482"},"institutions":[{"id":"https://openalex.org/I19722","display_name":"Ateneo de Manila University","ror":"https://ror.org/053kevk63","country_code":"PH","type":"education","lineage":["https://openalex.org/I19722"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Rosula S.J. Reyes","raw_affiliation_strings":["Department of Electronics, Computer, and Communications Engineering, Ateneo De Manila University, Quezon City, Philippines"],"affiliations":[{"raw_affiliation_string":"Department of Electronics, Computer, and Communications Engineering, Ateneo De Manila University, Quezon City, Philippines","institution_ids":["https://openalex.org/I19722"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030377440"],"corresponding_institution_ids":["https://openalex.org/I19722"],"apc_list":null,"apc_paid":null,"fwci":3.8205,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.94420914,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9448999762535095,"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"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9448999762535095,"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"}},{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9190999865531921,"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/T11446","display_name":"Mobile Health and mHealth Applications","score":0.9050999879837036,"subfield":{"id":"https://openalex.org/subfields/3600","display_name":"General Health Professions"},"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/random-forest","display_name":"Random forest","score":0.7762025594711304},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.710843563079834},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6921010613441467},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.6759355068206787},{"id":"https://openalex.org/keywords/telemedicine","display_name":"Telemedicine","score":0.6255562901496887},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5995560884475708},{"id":"https://openalex.org/keywords/android","display_name":"Android (operating system)","score":0.59013831615448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5244962573051453},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.5058926939964294},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.5055723190307617},{"id":"https://openalex.org/keywords/decision-tree-learning","display_name":"Decision tree learning","score":0.4902234673500061},{"id":"https://openalex.org/keywords/prenatal-care","display_name":"Prenatal care","score":0.487724632024765},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.44251394271850586},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.4304124712944031},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.42266032099723816},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4222589433193207},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.42142534255981445},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.215262770652771},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.12254214286804199},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10835957527160645}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7762025594711304},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.710843563079834},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6921010613441467},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.6759355068206787},{"id":"https://openalex.org/C2779891985","wikidata":"https://www.wikidata.org/wiki/Q46994","display_name":"Telemedicine","level":3,"score":0.6255562901496887},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5995560884475708},{"id":"https://openalex.org/C557433098","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android (operating system)","level":2,"score":0.59013831615448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5244962573051453},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.5058926939964294},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.5055723190307617},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.4902234673500061},{"id":"https://openalex.org/C2775887326","wikidata":"https://www.wikidata.org/wiki/Q3308829","display_name":"Prenatal care","level":3,"score":0.487724632024765},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.44251394271850586},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.4304124712944031},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.42266032099723816},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4222589433193207},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.42142534255981445},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.215262770652771},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.12254214286804199},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10835957527160645},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.0},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon50793.2020.9293890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon50793.2020.9293890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W643527848","https://openalex.org/W1530181845","https://openalex.org/W1603335467","https://openalex.org/W1984186688","https://openalex.org/W2005014092","https://openalex.org/W2014317722","https://openalex.org/W2018115628","https://openalex.org/W2019451125","https://openalex.org/W2032271311","https://openalex.org/W2141939314","https://openalex.org/W2185420312","https://openalex.org/W2363249082","https://openalex.org/W2463638724","https://openalex.org/W2597147203","https://openalex.org/W2626291538","https://openalex.org/W2807758217","https://openalex.org/W2883644528","https://openalex.org/W2886048309","https://openalex.org/W2921407969","https://openalex.org/W6620967642"],"related_works":["https://openalex.org/W4387490204","https://openalex.org/W4386414453","https://openalex.org/W4389848424","https://openalex.org/W4388937883","https://openalex.org/W4293205612","https://openalex.org/W4386566933","https://openalex.org/W4382052965","https://openalex.org/W4352976590","https://openalex.org/W4297839701","https://openalex.org/W4385349203"],"abstract_inverted_index":{"The":[0,60,134,183],"lack":[1],"of":[2,106,116,136,143,155,185,211],"health":[3,6,10,58],"professionals,":[4],"quality":[5,31],"care,":[7],"and":[8,14,22,33,57,83,91,130,147,157,179],"accessible":[9],"centers":[11],"in":[12,19,26,39,141,190],"rural":[13],"isolated":[15],"communities":[16],"have":[17],"resulted":[18],"high":[20],"maternal":[21,32],"fetal":[23],"mortality":[24],"rates":[25],"the":[27,48,89,100,114,117,148,152,163,168,174,198,209],"Philippines,":[28],"especially":[29],"since":[30],"child":[34],"healthcare":[35],"services":[36],"are":[37],"concentrated":[38],"more":[40],"developed":[41],"urban":[42],"areas.":[43],"This":[44],"study":[45],"proposes":[46],"applying":[47],"Telemedicine":[49,62],"framework":[50],"as":[51],"a":[52,68,75,85,92,104,201,213],"helping":[53],"tool":[54],"for":[55,79,88,113],"doctors":[56],"professionals.":[59],"implemented":[61,112],"approach":[63],"on":[64,160],"prenatal":[65],"care":[66],"followed":[67],"set-up":[69],"that":[70,195],"included":[71],"patient":[72,101,199],"information":[73],"input,":[74],"mobile":[76,193],"application":[77,194],"used":[78],"both":[80],"data":[81,98],"input":[82],"visualization,":[84],"cloud-based":[86],"server":[87],"database,":[90],"machine":[93,118],"learning":[94,119],"system":[95,120],"which":[96],"analyzed":[97],"from":[99],"profile.":[102],"With":[103],"dataset":[105],"97":[107],"samples,":[108],"four":[109],"algorithms":[110],"were":[111,188],"development":[115],"-":[121],"Decision":[122,126,171],"Tree,":[123,127],"Random":[124,169],"Forest":[125,170],"K-Nearest":[128],"Neighbor,":[129],"Support":[131],"Vector":[132],"Machine.":[133],"performance":[135],"each":[137],"algorithm":[138,166,187],"was":[139,167,200],"tested":[140],"terms":[142],"accuracy,":[144],"precision,":[145],"recall,":[146],"F1":[149],"score":[150,177,181],"or":[151,203],"weighted":[153],"average":[154],"precision":[156],"recall.":[158],"Based":[159],"these":[161],"parameters,":[162],"most":[164],"effective":[165],"Tree":[172],"with":[173,206],"highest":[175],"train":[176],"(0.987)":[178],"test":[180],"(0.900).":[182],"results":[184],"this":[186],"visualized":[189],"an":[191],"Android":[192],"displayed":[196],"whether":[197],"positive":[202],"negative":[204],"case":[205],"respect":[207],"to":[208],"possibility":[210],"having":[212],"high-risk":[214],"pregnancy.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}