{"id":"https://openalex.org/W4393970402","doi":"https://doi.org/10.1145/3644116.3644234","title":"Cluster-based Discovering of Disease Risk Factors: A COVID-19 Case Study","display_name":"Cluster-based Discovering of Disease Risk Factors: A COVID-19 Case Study","publication_year":2023,"publication_date":"2023-10-20","ids":{"openalex":"https://openalex.org/W4393970402","doi":"https://doi.org/10.1145/3644116.3644234"},"language":"en","primary_location":{"id":"doi:10.1145/3644116.3644234","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3644116.3644234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science","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/A5047201049","display_name":"Peixin Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peixin Zheng","raw_affiliation_strings":["School of Computer Science and Technology, Dongguan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Dongguan University of Technology, China","institution_ids":["https://openalex.org/I2799850029"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028303789","display_name":"Qunfeng Liu","orcid":"https://orcid.org/0000-0002-6286-941X"},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qunfeng Liu","raw_affiliation_strings":["School of Computer Science and Technology, Dongguan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Dongguan University of Technology, China","institution_ids":["https://openalex.org/I2799850029"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5095084440","display_name":"Yunchao Zhi","orcid":null},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunchao Zhi","raw_affiliation_strings":["School of Computer Science and Technology, Dongguan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Dongguan University of Technology, China","institution_ids":["https://openalex.org/I2799850029"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047201049"],"corresponding_institution_ids":["https://openalex.org/I2799850029"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36239448,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"706","last_page":"712"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9969000220298767,"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"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9969000220298767,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9955000281333923,"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/T11719","display_name":"Data Quality and Management","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.6805722713470459},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5826563835144043},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.567730188369751},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.44203850626945496},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21272066235542297},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.10021194815635681},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.0834590494632721},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07536903023719788}],"concepts":[{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.6805722713470459},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5826563835144043},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.567730188369751},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.44203850626945496},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21272066235542297},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.10021194815635681},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0834590494632721},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07536903023719788}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3644116.3644234","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3644116.3644234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science","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":11,"referenced_works":["https://openalex.org/W2030741364","https://openalex.org/W2036216970","https://openalex.org/W2167101736","https://openalex.org/W2240536489","https://openalex.org/W2395028581","https://openalex.org/W2520303620","https://openalex.org/W3172328600","https://openalex.org/W3210740940","https://openalex.org/W4200006435","https://openalex.org/W4206759694","https://openalex.org/W4281616267"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4382894326","https://openalex.org/W3035105474","https://openalex.org/W2390279801","https://openalex.org/W4205698903","https://openalex.org/W2358668433","https://openalex.org/W4294968941","https://openalex.org/W4283819461","https://openalex.org/W4390279739","https://openalex.org/W2376932109"],"abstract_inverted_index":{"As":[0],"the":[1,34,54,58,70,75,90,104,111,119,137,155],"amount":[2],"of":[3,24,36,57,60,94,103],"medical":[4,11,149],"data":[5,12,55,150],"continues":[6],"to":[7,88],"grow,":[8],"effectively":[9],"processing":[10],"and":[13,62,74,96,115,127,154],"extracting":[14],"key":[15,46,100],"information":[16,158],"from":[17,147],"it":[18],"has":[19],"become":[20],"an":[21],"important":[22,157],"area":[23],"research.":[25],"This":[26],"paper":[27,142],"presents":[28],"a":[29,41,144],"data-driven":[30],"exploration":[31],"process":[32],"in":[33],"field":[35],"artificial":[37],"intelligence":[38],"medicine,":[39],"with":[40,50,132],"special":[42],"focus":[43],"on":[44,53],"identifying":[45],"risk":[47,101,138],"factors":[48,102],"associated":[49],"COVID-19.":[51],"Based":[52],"characteristics":[56],"combination":[59],"categorical":[61],"numerical":[63],"variables,":[64],"feature":[65,116],"selection":[66],"was":[67,79,86],"performed":[68],"using":[69],"chi-square":[71],"test":[72],"method":[73],"initial":[76],"K":[77],"value":[78],"obtained":[80],"by":[81,109],"Canopy":[82],"algorithm,":[83],"then":[84],"NDP-Kmeans":[85],"used":[87],"divide":[89],"patients":[91],"into":[92],"clusters":[93],"diagnosed":[95],"undiagnosed":[97],"clusters.":[98,121],"The":[99,122],"disease":[105],"were":[106],"found":[107],"out":[108],"calculating":[110],"Pearson":[112],"correlation":[113],"coefficients":[114],"indices":[117],"within":[118],"two":[120],"results":[123],"indicates":[124],"that":[125],"diabetes":[126],"obesity":[128],"are":[129],"highly":[130],"correlated":[131],"COVID-19,":[133],"regarding":[134],"them":[135],"as":[136],"factors.":[139],"Furthermore,":[140],"this":[141],"provides":[143],"process-oriented":[145],"framework":[146],"which":[148],"can":[151,159],"be":[152,160],"processed":[153],"required":[156],"extracted.":[161]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}