{"id":"https://openalex.org/W4406460272","doi":"https://doi.org/10.1109/bigdata62323.2024.10825503","title":"Accounting for Cancer Patients with Severe Outcomes: An Anomaly Detection Perspective","display_name":"Accounting for Cancer Patients with Severe Outcomes: An Anomaly Detection Perspective","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406460272","doi":"https://doi.org/10.1109/bigdata62323.2024.10825503"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825503","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/A5081920875","display_name":"Yan Yang","orcid":"https://orcid.org/0000-0003-0131-7993"},"institutions":[{"id":"https://openalex.org/I196729704","display_name":"Southern Illinois University School of Medicine","ror":"https://ror.org/0232r4451","country_code":"US","type":"education","lineage":["https://openalex.org/I196729704","https://openalex.org/I2801502357"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yang Yan","raw_affiliation_strings":["Southern Illinois University,School of Computing"],"affiliations":[{"raw_affiliation_string":"Southern Illinois University,School of Computing","institution_ids":["https://openalex.org/I196729704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073087299","display_name":"C.E. Lominska","orcid":"https://orcid.org/0000-0003-1829-1371"},"institutions":[{"id":"https://openalex.org/I4210128618","display_name":"University of Kansas Medical Center","ror":"https://ror.org/036c9yv20","country_code":"US","type":"funder","lineage":["https://openalex.org/I4210128618"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Lominska","raw_affiliation_strings":["University of Kansas Medical Center,Department of Radiation Oncology"],"affiliations":[{"raw_affiliation_string":"University of Kansas Medical Center,Department of Radiation Oncology","institution_ids":["https://openalex.org/I4210128618"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044093871","display_name":"Gregory N. Gan","orcid":"https://orcid.org/0000-0001-5090-0064"},"institutions":[{"id":"https://openalex.org/I4210128618","display_name":"University of Kansas Medical Center","ror":"https://ror.org/036c9yv20","country_code":"US","type":"funder","lineage":["https://openalex.org/I4210128618"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gregory N Gan","raw_affiliation_strings":["University of Kansas Medical Center,Department of Radiation Oncology"],"affiliations":[{"raw_affiliation_string":"University of Kansas Medical Center,Department of Radiation Oncology","institution_ids":["https://openalex.org/I4210128618"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085096384","display_name":"Hao Gao","orcid":"https://orcid.org/0000-0002-4253-7418"},"institutions":[{"id":"https://openalex.org/I4210128618","display_name":"University of Kansas Medical Center","ror":"https://ror.org/036c9yv20","country_code":"US","type":"funder","lineage":["https://openalex.org/I4210128618"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Gao","raw_affiliation_strings":["University of Kansas Medical Center,Department of Radiation Oncology"],"affiliations":[{"raw_affiliation_string":"University of Kansas Medical Center,Department of Radiation Oncology","institution_ids":["https://openalex.org/I4210128618"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100430427","display_name":"Zhong Chen","orcid":"https://orcid.org/0000-0003-4755-9357"},"institutions":[{"id":"https://openalex.org/I196729704","display_name":"Southern Illinois University School of Medicine","ror":"https://ror.org/0232r4451","country_code":"US","type":"education","lineage":["https://openalex.org/I196729704","https://openalex.org/I2801502357"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhong Chen","raw_affiliation_strings":["Southern Illinois University,School of Computing"],"affiliations":[{"raw_affiliation_string":"Southern Illinois University,School of Computing","institution_ids":["https://openalex.org/I196729704"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5081920875"],"corresponding_institution_ids":["https://openalex.org/I196729704"],"apc_list":null,"apc_paid":null,"fwci":1.0848,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.82863502,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"8253","last_page":"8255"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.998199999332428,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.998199999332428,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.9314000010490417,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6613829135894775},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3989311456680298},{"id":"https://openalex.org/keywords/accounting","display_name":"Accounting","score":0.39773738384246826},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.33664512634277344},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.3318972885608673},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23421981930732727},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.22364386916160583}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6613829135894775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3989311456680298},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.39773738384246826},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.33664512634277344},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3318972885608673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23421981930732727},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.22364386916160583}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825503","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1974775928","https://openalex.org/W1986332411","https://openalex.org/W2016841028","https://openalex.org/W2019014808","https://openalex.org/W2031470922","https://openalex.org/W2056081083","https://openalex.org/W2105497548","https://openalex.org/W2106396955","https://openalex.org/W2109826612","https://openalex.org/W2125835628","https://openalex.org/W2183087644","https://openalex.org/W2296719434","https://openalex.org/W2336788611","https://openalex.org/W2603592198","https://openalex.org/W2900543659","https://openalex.org/W3001077607","https://openalex.org/W3011850127","https://openalex.org/W3102979309","https://openalex.org/W3107309379","https://openalex.org/W3126192485","https://openalex.org/W3139234154","https://openalex.org/W3165734808","https://openalex.org/W3171455733","https://openalex.org/W3203775877","https://openalex.org/W4205958143","https://openalex.org/W4225432572","https://openalex.org/W4253461361","https://openalex.org/W4254182148","https://openalex.org/W4281717669","https://openalex.org/W4296078751","https://openalex.org/W4312433903","https://openalex.org/W4318187150","https://openalex.org/W4319293695","https://openalex.org/W4378417908","https://openalex.org/W4386811891","https://openalex.org/W4388816595","https://openalex.org/W4402013540","https://openalex.org/W4402081437","https://openalex.org/W6607543680","https://openalex.org/W6685974025","https://openalex.org/W6703470281","https://openalex.org/W6838626697","https://openalex.org/W6886067055"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3031052312","https://openalex.org/W4389568370","https://openalex.org/W3032375762","https://openalex.org/W1995515455","https://openalex.org/W2080531066","https://openalex.org/W3108674512","https://openalex.org/W1506200166"],"abstract_inverted_index":{"Health":[0],"outcomes":[1,53,86,89],"and":[2,22,30,34,45,58,84,114,124],"radiation-induced":[3],"toxicities":[4],"for":[5,43,49,101,133],"cancer":[6,106],"patients":[7,50,81,107],"undergoing":[8],"radiation":[9],"therapy":[10],"are":[11,41],"influenced":[12],"by":[13,26,62,119],"several":[14],"factors,":[15],"including":[16],"the":[17,28,63,95,102],"disease":[18,29],"process,":[19],"treatment":[20],"plan,":[21],"various":[23],"symptoms":[24],"produced":[25],"both":[27,122],"treatment.":[31],"Accurate":[32],"prediction":[33],"assessment":[35],"of":[36,65,74],"a":[37,72],"patient\u2019s":[38],"health":[39,110],"status":[40],"pivotal":[42],"precision":[44],"personalized":[46],"healthcare,":[47],"especially":[48],"suffering":[51],"severe":[52,85,109],"such":[54],"as":[55],"pain,":[56],"depression,":[57],"sleep":[59],"disorders.":[60],"Motivated":[61],"issue":[64],"extreme":[66],"class":[67],"imbalance,":[68],"this":[69],"study":[70,128],"investigates":[71],"set":[73],"unsupervised":[75],"anomaly":[76],"detection":[77],"approaches":[78],"to":[79],"classify":[80],"with":[82,108],"mild/intermediate":[83],"using":[87],"patient-reported":[88],"(PROs)":[90],"datasets.":[91],"We":[92],"found":[93],"that":[94],"HBOS":[96],"method":[97],"demonstrated":[98],"superior":[99],"performance":[100],"minority":[103,125],"class,":[104],"representing":[105],"statuses.":[111],"Moreover,":[112],"IForest":[113],"KNN":[115],"showcased":[116],"good":[117],"potential":[118],"effectively":[120],"considering":[121],"majority":[123],"patients.":[126],"This":[127],"may":[129],"provide":[130],"insightful":[131],"guidelines":[132],"clinical":[134],"practice.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
