{"id":"https://openalex.org/W2077632029","doi":"https://doi.org/10.1109/bibm.2014.6999221","title":"Hospital pricing estimation by Gaussian conditional random fields based regression on graphs","display_name":"Hospital pricing estimation by Gaussian conditional random fields based regression on graphs","publication_year":2014,"publication_date":"2014-11-01","ids":{"openalex":"https://openalex.org/W2077632029","doi":"https://doi.org/10.1109/bibm.2014.6999221","mag":"2077632029"},"language":"en","primary_location":{"id":"doi:10.1109/bibm.2014.6999221","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2014.6999221","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5024490387","display_name":"Athanasia Polychronopoulou","orcid":null},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"A. Polychronopoulou","raw_affiliation_strings":["Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA, USA","Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA 19122, USA"],"affiliations":[{"raw_affiliation_string":"Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]},{"raw_affiliation_string":"Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA 19122, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044038055","display_name":"Zoran Obradovi\u0107","orcid":"https://orcid.org/0000-0002-2051-0142"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Z. Obradovic","raw_affiliation_strings":["Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA, USA","Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA 19122, USA"],"affiliations":[{"raw_affiliation_string":"Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]},{"raw_affiliation_string":"Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA 19122, USA","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5024490387"],"corresponding_institution_ids":["https://openalex.org/I84392919"],"apc_list":null,"apc_paid":null,"fwci":6.8227,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.96594059,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"21","issue":null,"first_page":"564","last_page":"567"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10804","display_name":"Health Systems, Economic Evaluations, Quality of Life","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10804","display_name":"Health Systems, Economic Evaluations, Quality of Life","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11773","display_name":"Healthcare Operations and Scheduling Optimization","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"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/T10136","display_name":"Statistical Methods and Inference","score":0.9799000024795532,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.5966247916221619},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5949693918228149},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.49770835041999817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47247716784477234},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4544031322002411},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4026889204978943},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.36934489011764526},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3668612837791443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31917881965637207},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.12562412023544312},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07472330331802368}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.5966247916221619},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5949693918228149},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.49770835041999817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47247716784477234},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4544031322002411},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4026889204978943},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.36934489011764526},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3668612837791443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31917881965637207},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.12562412023544312},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07472330331802368},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bibm.2014.6999221","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2014.6999221","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.696.2823","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.696.2823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.dabi.temple.edu/%7Ezoran/papers/BIBM_CCR_paper_short_final.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332467","display_name":"U.S. Air Force","ror":"https://ror.org/006gmme17"},{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W157394225","https://openalex.org/W1490716625","https://openalex.org/W1544526228","https://openalex.org/W1766290689","https://openalex.org/W1825077972","https://openalex.org/W2018389798","https://openalex.org/W2055921502","https://openalex.org/W2082113978","https://openalex.org/W2143908786","https://openalex.org/W2147880316","https://openalex.org/W2159973364","https://openalex.org/W4232037120","https://openalex.org/W6606454224","https://openalex.org/W6632618830","https://openalex.org/W6637989529","https://openalex.org/W6682082992","https://openalex.org/W6683277684"],"related_works":["https://openalex.org/W4255213289","https://openalex.org/W2890041053","https://openalex.org/W3021457118","https://openalex.org/W2037533603","https://openalex.org/W1976632465","https://openalex.org/W2058473841","https://openalex.org/W2955370177","https://openalex.org/W2095705902","https://openalex.org/W2602411199","https://openalex.org/W2094419952"],"abstract_inverted_index":{"Accurate":[0],"estimation":[1],"of":[2,16,79,96,148,168,175],"what":[3,11],"a":[4,7,93,123,157],"day":[5],"in":[6,61,137,150],"hospital":[8,13,45,47,86,152,164],"costs":[9],"and":[10,31,48,60],"the":[12,39,53,77,81,85,107,113,116,138,176,180],"charges":[14],"is":[15,36,56],"high":[17],"interest":[18],"to":[19,46,155],"many":[20],"parties,":[21],"including":[22],"health":[23,29],"care":[24],"providers,":[25],"medical":[26],"insurance":[27],"companies,":[28],"researchers,":[30],"uninsured":[32],"patients.":[33],"The":[34,145,166],"problem":[35,78],"complex,":[37],"as":[38,134],"cost-to-charge":[40,54,82,117,169,193,197],"ratio":[41,55,83,170,198],"varies":[42],"greatly":[43],"from":[44,67,106],"over":[49,102],"time.":[50],"In":[51,72,112,195],"addition,":[52,196],"often":[57],"not":[58],"reported,":[59],"such":[62],"cases":[63],"group":[64,190],"average":[65,191],"values":[66],"similar":[68],"hospitals":[69,121],"are":[70],"used.":[71],"this":[73],"study":[74],"we":[75],"address":[76],"estimating":[80],"at":[84,119],"level":[87],"by":[88,127,200,206],"utilizing":[89],"structured":[90],"regression":[91,205],"on":[92,179,189],"temporal":[94],"graph":[95,182],"more":[97],"than":[98,186],"4,000":[99],"hospitals,":[100],"observed":[101],"8":[103],"years,":[104],"constructed":[105,181],"National":[108],"Inpatient":[109],"Sample":[110],"database.":[111],"proposed":[114],"approach,":[115],"estimates":[118,167,199],"individual":[120],"for":[122],"certain":[124],"month":[125],"obtained":[126,171],"an":[128],"artificial":[129,208],"neural":[130,209],"network":[131],"were":[132,153,183],"used":[133,154],"unstructured":[135],"components":[136],"Gaussian":[139],"Conditional":[140],"Random":[141],"Fields":[142],"(GCRF)":[143],"model.":[144],"diagnosis":[146],"codes":[147],"treatments":[149],"each":[151],"create":[156],"similarity":[158],"metric":[159],"that":[160],"represents":[161],"correlation":[162],"among":[163],"specializations.":[165],"using":[172],"convex":[173],"optimization":[174],"GCRF":[177,202],"parameters":[178],"much":[184],"better":[185],"those":[187],"relying":[188],"based":[192],"estimates.":[194],"our":[201],"model":[203],"outperformed":[204],"nonlinear":[207],"networks.":[210]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}