{"id":"https://openalex.org/W3195431630","doi":"https://doi.org/10.1145/3469830.3470903","title":"Clustering of Adverse Events of Post-Market Approved Drugs","display_name":"Clustering of Adverse Events of Post-Market Approved Drugs","publication_year":2021,"publication_date":"2021-08-19","ids":{"openalex":"https://openalex.org/W3195431630","doi":"https://doi.org/10.1145/3469830.3470903","mag":"3195431630"},"language":"en","primary_location":{"id":"doi:10.1145/3469830.3470903","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469830.3470903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"17th International Symposium on Spatial and Temporal Databases","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/A5101726502","display_name":"Ahmed Askar","orcid":"https://orcid.org/0000-0002-4537-5418"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ahmed Askar","raw_affiliation_strings":["George Mason University, United States"],"affiliations":[{"raw_affiliation_string":"George Mason University, United States","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037401272","display_name":"Andreas Zuefle","orcid":null},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas Zuefle","raw_affiliation_strings":["George Mason University, United States"],"affiliations":[{"raw_affiliation_string":"George Mason University, United States","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101726502"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63034349,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"106","last_page":"115"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14351","display_name":"Statistical and Computational Modeling","score":0.949999988079071,"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/T14351","display_name":"Statistical and Computational Modeling","score":0.949999988079071,"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/T12878","display_name":"Pharmaceutical Quality and Counterfeiting","score":0.9361000061035156,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7251026034355164},{"id":"https://openalex.org/keywords/adverse-effect","display_name":"Adverse effect","score":0.5152133107185364},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3805712163448334},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3377370238304138},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3274141550064087},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.31887713074684143},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.26830869913101196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2152949869632721}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7251026034355164},{"id":"https://openalex.org/C197934379","wikidata":"https://www.wikidata.org/wiki/Q2047938","display_name":"Adverse effect","level":2,"score":0.5152133107185364},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3805712163448334},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3377370238304138},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3274141550064087},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.31887713074684143},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.26830869913101196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2152949869632721}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3469830.3470903","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469830.3470903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"17th International Symposium on Spatial and Temporal Databases","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W980260691","https://openalex.org/W1880262756","https://openalex.org/W2001589423","https://openalex.org/W2012757283","https://openalex.org/W2035890032","https://openalex.org/W2052611179","https://openalex.org/W2066240751","https://openalex.org/W2086371138","https://openalex.org/W2113855231","https://openalex.org/W2135631383","https://openalex.org/W2136230731","https://openalex.org/W2157398916","https://openalex.org/W2319116535","https://openalex.org/W2331487051","https://openalex.org/W2479940738","https://openalex.org/W2523933248","https://openalex.org/W2740924709","https://openalex.org/W2786016794","https://openalex.org/W2885241551","https://openalex.org/W2966993688","https://openalex.org/W2998942685","https://openalex.org/W4210779690","https://openalex.org/W4298290504"],"related_works":["https://openalex.org/W4391375266","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","https://openalex.org/W1489783725"],"abstract_inverted_index":{"Adverse":[0,49],"side":[1,22],"effects":[2,23,37,96,151],"of":[3,65,93,109,117,163],"a":[4,31,72,86,103,107],"drug":[5,18,32,129],"may":[6,152],"vary":[7],"over":[8],"space":[9],"and":[10,17,42,44,58],"time":[11],"due":[12],"to":[13,76,142],"different":[14],"populations,":[15],"environments,":[16],"quality.":[19],"Discovering":[20],"all":[21],"during":[24],"the":[25,48,55,110,127,136,144],"development":[26],"process":[27],"is":[28,33],"impossible.":[29],"Once":[30],"approved,":[34],"observed":[35],"adverse":[36,67,82,95,124,150],"are":[38],"reported":[39,66,94],"by":[40,54],"doctors":[41],"patients":[43],"made":[45],"available":[46],"in":[47,155],"Event":[50],"Reporting":[51],"System":[52],"provided":[53],"U.S.":[56],"Food":[57],"Drug":[59],"Administration":[60],".":[61],"Mining":[62],"such":[63],"records":[64],"effects,":[68],"this":[69],"study":[70],"proposes":[71],"spatial":[73,104,140,157,164],"clustering":[74],"approach":[75,89],"identify":[77],"regions":[78,118,158],"that":[79,119,146],"exhibit":[80,120],"similar":[81,121],"effects.":[83],"We":[84,134],"apply":[85],"topic":[87],"modeling":[88],"on":[90],"textual":[91],"representations":[92],"using":[97,130,159],"Latent":[98],"Dirichlet":[99],"Allocation.":[100],"By":[101],"describing":[102],"region":[105],"as":[106],"mixture":[108],"resulting":[111,137],"latent":[112],"topics,":[113],"we":[114],"find":[115],"clusters":[116,138],"(topics":[122,148],"of)":[123,149],"events":[125],"for":[126,139],"same":[128],"Hierarchical":[131],"Agglomerative":[132],"Clustering.":[133],"investigate":[135],"autocorrelation":[141],"test":[143],"hypothesis":[145],"certain":[147,156],"occur":[153],"only":[154],"Moran\u2019s":[160],"I":[161],"measure":[162],"autocorrelation.":[165]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
