{"id":"https://openalex.org/W2014906038","doi":"https://doi.org/10.1016/j.procs.2014.05.164","title":"Historical Claims Data based Hybrid Predictive Models for Hospitalization","display_name":"Historical Claims Data based Hybrid Predictive Models for Hospitalization","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2014906038","doi":"https://doi.org/10.1016/j.procs.2014.05.164","mag":"2014906038"},"language":"en","primary_location":{"id":"doi:10.1016/j.procs.2014.05.164","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2014.05.164","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1016/j.procs.2014.05.164","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112345326","display_name":"Chengcheng Liu","orcid":"https://orcid.org/0000-0003-2504-4627"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengcheng Liu","raw_affiliation_strings":["School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, China","School of Computer and Control Engineering, University of Chinese, Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"School of Computer and Control Engineering, University of Chinese, Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113542097","display_name":"Yong Shi","orcid":"https://orcid.org/0000-0001-7974-1079"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yong Shi","raw_affiliation_strings":["Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5112345326","https://openalex.org/A5113542097"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"29","issue":null,"first_page":"1791","last_page":"1800"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9922999739646912,"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"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9922999739646912,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9545000195503235,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9289000034332275,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/mean-squared-error","display_name":"Mean squared error","score":0.7638459205627441},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7436233758926392},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.6353344917297363},{"id":"https://openalex.org/keywords/mean-squared-prediction-error","display_name":"Mean squared prediction error","score":0.47888821363449097},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.47662293910980225},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.47347012162208557},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.42128023505210876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38823291659355164},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38531437516212463},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3743065893650055},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.30448561906814575},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.16133970022201538},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09249567985534668}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.7638459205627441},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7436233758926392},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.6353344917297363},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.47888821363449097},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.47662293910980225},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.47347012162208557},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.42128023505210876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38823291659355164},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38531437516212463},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3743065893650055},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.30448561906814575},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.16133970022201538},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09249567985534668},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.procs.2014.05.164","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2014.05.164","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.procs.2014.05.164","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2014.05.164","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W2025126442","https://openalex.org/W2069904247","https://openalex.org/W4253223262"],"related_works":["https://openalex.org/W2621951291","https://openalex.org/W4319441652","https://openalex.org/W4295442786","https://openalex.org/W4386715265","https://openalex.org/W2974739419","https://openalex.org/W2811187992","https://openalex.org/W3042921537","https://openalex.org/W803509314","https://openalex.org/W1995617853","https://openalex.org/W2132491819"],"abstract_inverted_index":{"Over":[0],"$30":[1],"billion":[2],"are":[3,24],"wasted":[4],"on":[5,66,97],"unnecessary":[6],"hospitalization":[7,136],"each":[8],"year,":[9],"therefore":[10],"it":[11,123],"is":[12,72,95,124],"needed":[13],"to":[14,20,27,47,52,126,134],"find":[15],"a":[16,37,49],"better":[17],"quantitative":[18],"way":[19],"identify":[21],"patients":[22,57],"who":[23],"mostly":[25],"likely":[26],"be":[28],"hospitalized":[29],"and":[30,90,113,137],"then":[31],"provide":[32],"them":[33],"utmost":[34],"care.":[35],"As":[36],"good":[38],"starting":[39],"point,":[40],"the":[41,61,75,85,103,114,132],"objective":[42],"of":[43,87,102,141],"this":[44],"paper":[45],"was":[46,111,119],"develop":[48],"predictive":[50,82,129],"model":[51,83,94],"predict":[53,135],"how":[54],"many":[55],"days":[56],"may":[58],"spend":[59],"in":[60,100],"hospital":[62],"next":[63],"year":[64],"based":[65],"patients\u2019":[67,139],"historical":[68],"claims":[69],"dataset,":[70],"which":[71],"provided":[73],"by":[74],"Heritage":[76],"Health":[77],"Prize":[78],"Competition.":[79],"The":[80,93,107],"proposed":[81],"applied":[84],"ensemble":[86],"binary":[88],"classification":[89],"regression":[91],"techniques.":[92],"evaluated":[96],"testing":[98],"dataset":[99],"terms":[101],"Root-Mean-":[104],"Square-Error":[105],"(RMSE).":[106],"best":[108],"RMSE":[109],"score":[110],"0.474,":[112],"corresponding":[115],"prediction":[116],"accuracy":[117],"81.9%":[118],"reasonably":[120],"high.":[121],"Therefore":[122],"convincing":[125],"conclude":[127],"that":[128],"models":[130],"have":[131],"potentials":[133],"improve":[138],"quality":[140],"life.":[142]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
