{"id":"https://openalex.org/W3086140553","doi":"https://doi.org/10.1109/icbk50248.2020.00026","title":"Imbalanced Learning for Hospital Readmission Prediction using National Readmission Database","display_name":"Imbalanced Learning for Hospital Readmission Prediction using National Readmission Database","publication_year":2020,"publication_date":"2020-08-01","ids":{"openalex":"https://openalex.org/W3086140553","doi":"https://doi.org/10.1109/icbk50248.2020.00026","mag":"3086140553"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbk50248.2020.00026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5100748345","display_name":"Shuwen Wang","orcid":"https://orcid.org/0000-0003-1899-9628"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuwen Wang","raw_affiliation_strings":["Department of Computer& Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer& Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088009593","display_name":"Magdalyn E. Elkin","orcid":"https://orcid.org/0000-0003-0651-0696"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Magdalyn E. Elkin","raw_affiliation_strings":["Department of Computer& Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer& Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084641325","display_name":"Xingquan Zhu","orcid":"https://orcid.org/0000-0003-4129-9611"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingquan Zhu","raw_affiliation_strings":["Department of Computer& Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer& Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, USA","institution_ids":["https://openalex.org/I63772739"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.357,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.630057,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":73,"max":77},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.984,"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":0.984,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9698,"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/T13970","display_name":"Pharmacy and Medical Practices","score":0.949,"subfield":{"id":"https://openalex.org/subfields/3004","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/national-database","display_name":"National database","score":0.44557196},{"id":"https://openalex.org/keywords/hospital-readmission","display_name":"Hospital Readmission","score":0.42174068}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.60606366},{"id":"https://openalex.org/C3018723762","wikidata":"https://www.wikidata.org/wiki/Q3071343","display_name":"National database","level":2,"score":0.44557196},{"id":"https://openalex.org/C2776644030","wikidata":"https://www.wikidata.org/wiki/Q25324519","display_name":"Hospital readmission","level":2,"score":0.42174068},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3616261},{"id":"https://openalex.org/C194828623","wikidata":"https://www.wikidata.org/wiki/Q2861470","display_name":"Emergency medicine","level":1,"score":0.26103026},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1919924}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbk50248.2020.00026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.47,"display_name":"Quality education"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":16,"referenced_works":["https://openalex.org/W1479917715","https://openalex.org/W170714584","https://openalex.org/W1996796871","https://openalex.org/W1999541429","https://openalex.org/W2016519398","https://openalex.org/W2085746458","https://openalex.org/W2089546043","https://openalex.org/W2110796408","https://openalex.org/W2144192049","https://openalex.org/W2160865775","https://openalex.org/W2170131723","https://openalex.org/W2553485720","https://openalex.org/W2596602780","https://openalex.org/W2736131889","https://openalex.org/W2923546398","https://openalex.org/W4242010285"],"related_works":["https://openalex.org/W2947115094","https://openalex.org/W2748952813","https://openalex.org/W2478288626","https://openalex.org/W2462473962","https://openalex.org/W2390279801","https://openalex.org/W2382290278","https://openalex.org/W2376932109","https://openalex.org/W2358668433","https://openalex.org/W2084687562","https://openalex.org/W2001405890"],"abstract_inverted_index":{"In":[0],"this":[1,128],"paper,":[2,129],"we":[3,130,172],"propose":[4],"to":[5,16,31,82,100,136,169,177,191,205],"use":[6],"imbalanced":[7,133],"learning":[8,134],"for":[9,78,90,120],"hospital":[10,25,44,50,70,141],"readmission":[11,51,57],"prediction.":[12],"The":[13,46],"goal":[14],"is":[15,28,53,93,96],"predict":[17,206],"whether":[18],"a":[19,64,73,113,182],"patient,":[20],"based":[21],"on":[22],"his/her":[23],"current":[24,43],"visit":[26,176],"records,":[27],"likely":[29],"going":[30],"be":[32],"re-admitted":[33],"or":[34],"not":[35],"within":[36],"30-days":[37],"after":[38],"being":[39],"discharged":[40],"from":[41,139],"the":[42,56,60,68,87,101,124,193,197],"visit.":[45],"main":[47],"challenge":[48],"of":[49,67,164],"prediction":[52],"twofold:":[54],"(1)":[55],"visits":[58],"(i.e.,":[59],"positive":[61],"class)":[62],"are":[63,107],"small":[65],"portion":[66],"total":[69],"visits,":[71],"representing":[72,112],"severe":[74],"class":[75],"imbalance":[76],"problem":[77,119],"learning;":[79],"(2)":[80],"due":[81],"privacy":[83],"and":[84,95,116,152,156],"health":[85],"regulation,":[86],"information":[88],"available":[89],"patient":[91,140,145,207],"characterization":[92],"limited;":[94],"often":[97],"only":[98],"limited":[99],"payment":[102],"level":[103],"information.":[104],"However,":[105],"there":[106],"over":[108],"80,000":[109],"procedures":[110],"code,":[111],"high":[114,117],"dimensionality":[115],"sparsity":[118],"learning.":[121],"Motivated":[122],"by":[123,143],"above":[125],"challenges,":[126],"in":[127,196],"design":[131],"an":[132],"strategy":[135],"create":[137],"features":[138],"visit,":[142],"combining":[144],"demographic":[146],"information,":[147],"ICD-10":[148],"clinical":[149],"modification":[150],"(CM)":[151],"procedure":[153],"codes":[154],"(PCS),":[155],"Clinical":[157],"Classification":[158],"Software":[159],"Refined":[160],"(CCSR)":[161],"conversion.":[162],"Instead":[163],"directly":[165],"using":[166,187],"ICD-10-CM/PCS":[167],"code":[168,179],"characterize":[170],"patients,":[171],"convert":[173],"each":[174],"patient's":[175],"CCSR":[178],"space":[180],"with":[181],"smaller":[183],"feature":[184],"space.":[185],"By":[186],"random":[188],"sampling":[189],"approach":[190],"balance":[192],"sample":[194],"distributions":[195],"training":[198],"set,":[199],"our":[200],"method":[201],"achieves":[202],"good":[203],"performance":[204],"readmission.":[208]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3086140553","counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-01-05T19:39:57.840345","created_date":"2020-09-21"}