{"id":"https://openalex.org/W4383334573","doi":"https://doi.org/10.1109/icaia57370.2023.10169737","title":"Machine Learning Models for Life Expectancy","display_name":"Machine Learning Models for Life Expectancy","publication_year":2023,"publication_date":"2023-04-21","ids":{"openalex":"https://openalex.org/W4383334573","doi":"https://doi.org/10.1109/icaia57370.2023.10169737"},"language":"en","primary_location":{"id":"doi:10.1109/icaia57370.2023.10169737","doi":"https://doi.org/10.1109/icaia57370.2023.10169737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaia57370.2023.10169737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5114760172","display_name":"Deepanshi Jalan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Deepanshi Jalan","raw_affiliation_strings":["Indira Gandhi DTU for Women,Department of Electronics and Communication with AI,Delhi,India","Department of Electronics and Communication with AI, Indira Gandhi DTU for Women, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indira Gandhi DTU for Women,Department of Electronics and Communication with AI,Delhi,India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Department of Electronics and Communication with AI, Indira Gandhi DTU for Women, Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114064527","display_name":"Anandita Tuli","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anandita Tuli","raw_affiliation_strings":["Indira Gandhi DTU for Women,Department of Electronics and Communication with AI,Delhi,India","Department of Electronics and Communication with AI, Indira Gandhi DTU for Women, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indira Gandhi DTU for Women,Department of Electronics and Communication with AI,Delhi,India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Department of Electronics and Communication with AI, Indira Gandhi DTU for Women, Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102532218","display_name":"Vanshika Chaudhary","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vanshika Chaudhary","raw_affiliation_strings":["Indira Gandhi DTU for Women,Department of Electronics and Communication with AI,Delhi,India","Department of Electronics and Communication with AI, Indira Gandhi DTU for Women, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indira Gandhi DTU for Women,Department of Electronics and Communication with AI,Delhi,India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Department of Electronics and Communication with AI, Indira Gandhi DTU for Women, Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031798370","display_name":"Nonita Sharma","orcid":"https://orcid.org/0000-0002-3132-3748","observed_orcids":["https://orcid.org/0000-0002-3132-3748"]},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nonita Sharma","raw_affiliation_strings":["Indira Gandhi DTU for Women,Department of Information Technology,Delhi,India","Department of Information Technology, Indira Gandhi DTU for Women, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indira Gandhi DTU for Women,Department of Information Technology,Delhi,India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Department of Information Technology, Indira Gandhi DTU for Women, Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065960093","display_name":"Manik Rakhra","orcid":"https://orcid.org/0000-0003-1680-6992","observed_orcids":["https://orcid.org/0000-0003-1680-6992"]},"institutions":[{"id":"https://openalex.org/I110360157","display_name":"Lovely Professional University","ror":"https://ror.org/00et6q107","country_code":"IN","type":"education","lineage":["https://openalex.org/I110360157"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manik Rakhra","raw_affiliation_strings":["Lovely Professional University,Department of Computer Science and Engineering,Phagwara,India","Department of Computer Science and Engineering, Lovely Professional University, Phagwara, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lovely Professional University,Department of Computer Science and Engineering,Phagwara,India","institution_ids":["https://openalex.org/I110360157"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Lovely Professional University, Phagwara, India","institution_ids":["https://openalex.org/I110360157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.3057,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.97041733,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.8335000276565552,"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"}},"topics":[{"id":"https://openalex.org/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.8335000276565552,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.09950000047683716,"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/T12781","display_name":"Global Health Care Issues","score":0.052000001072883606,"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/life-expectancy","display_name":"life expectancy","score":0.9959999918937683},{"id":"https://openalex.org/keywords/life-expectancy-trends","display_name":"life expectancy trends","score":0.9290000200271606},{"id":"https://openalex.org/keywords/gross-domestic-product","display_name":"gross domestic product","score":0.6150000095367432},{"id":"https://openalex.org/keywords/infant-mortality","display_name":"infant mortality","score":0.9890000224113464},{"id":"https://openalex.org/keywords/adult-mortality","display_name":"adult mortality","score":1.0},{"id":"https://openalex.org/keywords/cross-national-comparison","display_name":"cross-national comparison","score":0.6119999885559082},{"id":"https://openalex.org/keywords/health-policy","display_name":"health policy","score":0.6079999804496765},{"id":"https://openalex.org/keywords/retirement-age","display_name":"retirement age","score":0.5740000009536743},{"id":"https://openalex.org/keywords/public-finance","display_name":"public finance","score":0.3449999988079071}],"concepts":[{"id":"https://openalex.org/C133925201","wikidata":"https://www.wikidata.org/wiki/Q188419","display_name":"Life expectancy","level":3,"score":0.9090911149978638},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5734624266624451},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5568267703056335},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4989461898803711},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4668505787849426},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.43283629417419434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.334805428981781},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.18726995587348938},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.17013439536094666},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaia57370.2023.10169737","doi":"https://doi.org/10.1109/icaia57370.2023.10169737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaia57370.2023.10169737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.4043000042438507}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2059850157","https://openalex.org/W2101876347","https://openalex.org/W2796397915","https://openalex.org/W2942927933","https://openalex.org/W2943526108","https://openalex.org/W3138694636","https://openalex.org/W3139717453","https://openalex.org/W3194550749","https://openalex.org/W3205483668","https://openalex.org/W3212971215","https://openalex.org/W3214118962","https://openalex.org/W4238065897","https://openalex.org/W4282840942","https://openalex.org/W4304208130","https://openalex.org/W4309639804","https://openalex.org/W4312472510","https://openalex.org/W6789549879"],"related_works":["https://openalex.org/W3212971215","https://openalex.org/W4410295275","https://openalex.org/W4365145377","https://openalex.org/W4380988909","https://openalex.org/W3138694636","https://openalex.org/W7159943051","https://openalex.org/W4407198929","https://openalex.org/W7171776636","https://openalex.org/W4323438521","https://openalex.org/W4412558797"],"abstract_inverted_index":{"Life":[0,19,79],"expectancy":[1,20,123,143],"(LE)":[2],"models":[3,21,42],"provide":[4,22],"a":[5,89],"lot":[6],"of":[7,85,91,101,128,144,177],"ways":[8],"to":[9,17,24,28,38,74,138],"improve":[10],"healthcare":[11],"and":[12,58,65,130,173,185],"other":[13],"social":[14],"welfares":[15],"related":[16,37],"society.":[18],"solutions":[23],"problems":[25],"like":[26,159],"how":[27],"decide":[29],"on":[30],"retirement":[31],"age":[32],"or":[33],"manage":[34],"financial":[35],"issues":[36],"public":[39],"matters.":[40],"These":[41],"are":[43,51,149],"becoming":[44],"prominent":[45],"in":[46,78,81,151],"many":[47],"regions":[48],"as":[49,104],"they":[50],"being":[52],"widely":[53],"used":[54],"by":[55,154],"government":[56],"bodies":[57],"private":[59],"sector":[60],"for":[61,164,169,181,189],"their":[62],"policy":[63],"making":[64],"developing":[66],"health":[67],"integrated":[68],"systems.":[69],"Thus,":[70],"this":[71],"paper":[72],"aims":[73],"analyze":[75],"the":[76,86,118,121,126,141],"Trends":[77],"Expectancy":[80],"about":[82],"72":[83],"countries":[84,119],"world":[87],"over":[88,125],"span":[90],"16":[92],"years,":[93],"i.e.,":[94],"from":[95],"2000-2015.":[96],"The":[97,147],"study":[98],"gives":[99],"plots":[100],"attributes":[102],"such":[103],"life":[105,122,142],"expectancy,":[106],"GDP,":[107],"infant":[108],"deaths,":[109],"adult":[110],"mortality,":[111],"etc.":[112],"across":[113],"year":[114],"which":[115,133],"would":[116],"help":[117],"understand":[120],"trends":[124],"course":[127],"time":[129],"suggest":[131],"areas":[132],"should":[134],"be":[135],"focused":[136],"upon":[137],"efficiently":[139],"increase":[140],"its":[145],"population.":[146],"simulations":[148],"done":[150],"Google":[152],"Collab":[153],"using":[155],"various":[156],"Python":[157],"libraries":[158],"pandas,":[160],"numpy,":[161],"matplotlib":[162],"(used":[163,168,180,188],"plotting":[165,170,190],"graphs),":[166],"seaborn":[167],"3-D":[171],"graphs":[172],"advanced":[174],"visualization":[175],"features":[176],"python),":[178],"sklearn":[179],"handling":[182],"missing":[183],"data),":[184],"plotly":[186],"express":[187],"choropleth).":[191]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":7}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2023-07-07T00:00:00"}
