{"id":"https://openalex.org/W4406458853","doi":"https://doi.org/10.1109/bigdata62323.2024.10826019","title":"Tackling No-show Imbalance problems for Healthcare Appointment datasets","display_name":"Tackling No-show Imbalance problems for Healthcare Appointment datasets","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458853","doi":"https://doi.org/10.1109/bigdata62323.2024.10826019"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10826019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10826019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5100379572","display_name":"Xiaoguang Wang","orcid":"https://orcid.org/0000-0002-5598-062X"},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Xiaoguang Wang","raw_affiliation_strings":["Dalhousie University,Dimension Institute,Halifax,NS,Canada"],"affiliations":[{"raw_affiliation_string":"Dalhousie University,Dimension Institute,Halifax,NS,Canada","institution_ids":["https://openalex.org/I129902397"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100362330","display_name":"Xuan Liu","orcid":"https://orcid.org/0000-0002-7966-4488"},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xuan Liu","raw_affiliation_strings":["Dalhousie University,Institute for Big Data Analytics,Halifax,NS,Canada"],"affiliations":[{"raw_affiliation_string":"Dalhousie University,Institute for Big Data Analytics,Halifax,NS,Canada","institution_ids":["https://openalex.org/I129902397"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100379572"],"corresponding_institution_ids":["https://openalex.org/I129902397"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44983278,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5086","last_page":"8095"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11773","display_name":"Healthcare Operations and Scheduling Optimization","score":0.9904999732971191,"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"}},"topics":[{"id":"https://openalex.org/T11773","display_name":"Healthcare Operations and Scheduling Optimization","score":0.9904999732971191,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9796000123023987,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9751999974250793,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.644029438495636},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.572282075881958},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.35616254806518555},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.09914246201515198}],"concepts":[{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.644029438495636},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.572282075881958},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35616254806518555},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.09914246201515198},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10826019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10826019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":102,"referenced_works":["https://openalex.org/W146900863","https://openalex.org/W571200655","https://openalex.org/W1485073568","https://openalex.org/W1550553906","https://openalex.org/W1563938718","https://openalex.org/W1579385792","https://openalex.org/W1581797854","https://openalex.org/W1850527962","https://openalex.org/W1975896808","https://openalex.org/W1978348970","https://openalex.org/W1985930887","https://openalex.org/W1986497662","https://openalex.org/W1988790447","https://openalex.org/W1993680757","https://openalex.org/W1999318832","https://openalex.org/W2008041363","https://openalex.org/W2013983862","https://openalex.org/W2022477494","https://openalex.org/W2023496240","https://openalex.org/W2037237663","https://openalex.org/W2040181375","https://openalex.org/W2051553229","https://openalex.org/W2053139876","https://openalex.org/W2091733371","https://openalex.org/W2093063118","https://openalex.org/W2094971193","https://openalex.org/W2096945460","https://openalex.org/W2104167780","https://openalex.org/W2104933073","https://openalex.org/W2104955141","https://openalex.org/W2107138773","https://openalex.org/W2107325824","https://openalex.org/W2110195956","https://openalex.org/W2118978333","https://openalex.org/W2119191234","https://openalex.org/W2132791018","https://openalex.org/W2136256517","https://openalex.org/W2141921295","https://openalex.org/W2146444359","https://openalex.org/W2148143831","https://openalex.org/W2163505464","https://openalex.org/W2171261673","https://openalex.org/W2213780140","https://openalex.org/W2277023526","https://openalex.org/W2346644295","https://openalex.org/W2559618712","https://openalex.org/W2562319768","https://openalex.org/W2593429137","https://openalex.org/W2595588825","https://openalex.org/W2604207036","https://openalex.org/W2606666966","https://openalex.org/W2610871088","https://openalex.org/W2616891418","https://openalex.org/W2749106997","https://openalex.org/W2753047523","https://openalex.org/W2770113078","https://openalex.org/W2789729126","https://openalex.org/W2790539339","https://openalex.org/W2791071944","https://openalex.org/W2793526893","https://openalex.org/W2802684173","https://openalex.org/W2888200901","https://openalex.org/W2891591134","https://openalex.org/W2900279086","https://openalex.org/W2900887514","https://openalex.org/W2903121257","https://openalex.org/W2908374243","https://openalex.org/W2909851383","https://openalex.org/W2912407815","https://openalex.org/W2913440910","https://openalex.org/W2929506125","https://openalex.org/W2936379053","https://openalex.org/W2953743058","https://openalex.org/W2967723897","https://openalex.org/W2979180284","https://openalex.org/W2981874965","https://openalex.org/W2995616570","https://openalex.org/W2996516141","https://openalex.org/W3017752926","https://openalex.org/W3024449563","https://openalex.org/W3031232306","https://openalex.org/W3111963617","https://openalex.org/W3137546229","https://openalex.org/W3155649056","https://openalex.org/W3213131041","https://openalex.org/W4224211318","https://openalex.org/W4283734711","https://openalex.org/W4294690789","https://openalex.org/W4307264886","https://openalex.org/W4318275401","https://openalex.org/W4385568380","https://openalex.org/W4388231274","https://openalex.org/W4390605457","https://openalex.org/W6603460400","https://openalex.org/W6639048329","https://openalex.org/W6675785006","https://openalex.org/W6745609711","https://openalex.org/W6750523955","https://openalex.org/W6765188188","https://openalex.org/W6794784816","https://openalex.org/W6803675131","https://openalex.org/W7053126446"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Medical":[0],"appointment":[1],"no-shows":[2],"have":[3,25],"a":[4,66,89,104,158],"significant":[5],"impact":[6],"on":[7,133,150],"the":[8,29,41,57,81,113,119,128,142,155],"revenue,":[9],"cost":[10],"and":[11,103,154],"resource":[12],"utilization":[13],"for":[14,36,70,122],"almost":[15],"all":[16,100],"healthcare":[17],"systems.":[18],"To":[19],"address":[20],"this":[21],"problem,":[22],"numerous":[23],"efforts":[24],"been":[26,54],"made":[27],"in":[28,49,161],"past":[30],"to":[31,92,131,165],"apply":[32],"machine":[33],"learning":[34],"algorithms":[35],"predicting":[37],"patient":[38],"no-shows.":[39],"However,":[40],"issue":[42],"of":[43,61,77,80,107,141],"class":[44],"imbalance":[45],"that":[46,72],"often":[47],"arises":[48],"these":[50],"cases":[51],"has":[52],"largely":[53],"neglected.":[55],"Given":[56],"highly":[58],"imbalanced":[59],"nature":[60],"our":[62,147],"data,":[63],"we":[64],"propose":[65],"novel":[67],"ensemble":[68],"method":[69,84,149],"classification":[71,162],"generates":[73],"an":[74],"arbitrary":[75],"number":[76],"balanced":[78,94,135],"splits":[79],"data.":[82,144],"This":[83,125],"uses":[85],"Instance":[86],"Hardness":[87],"as":[88,118],"weighting":[90],"mechanism":[91],"create":[93],"bags,":[95,136],"with":[96],"each":[97,123,137],"bag":[98],"containing":[99],"minority":[101],"instances":[102],"filtered":[105],"subset":[106],"majority":[108],"instances.":[109],"We":[110,145],"then":[111],"employ":[112],"Histogram-based":[114],"Gradient":[115],"Boosting":[116],"classifier":[117],"base":[120,129],"learner":[121],"bag.":[124],"approach":[126],"allows":[127],"learners":[130],"train":[132],"different":[134],"reflecting":[138],"varied":[139],"characteristics":[140],"training":[143],"tested":[146],"proposed":[148],"four":[151],"no-show":[152],"datasets,":[153],"results":[156],"demonstrate":[157],"substantial":[159],"improvement":[160],"performance":[163],"compared":[164],"other":[166],"methods.":[167]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
