{"id":"https://openalex.org/W7135246144","doi":"https://doi.org/10.1109/iccp68926.2025.11427139","title":"Adverse Event Detection in medical documents -Non-Pharmaceutical Substances","display_name":"Adverse Event Detection in medical documents -Non-Pharmaceutical Substances","publication_year":2025,"publication_date":"2025-10-16","ids":{"openalex":"https://openalex.org/W7135246144","doi":"https://doi.org/10.1109/iccp68926.2025.11427139"},"language":null,"primary_location":{"id":"doi:10.1109/iccp68926.2025.11427139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp68926.2025.11427139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Intelligent Computer Communication and Processing (ICCP)","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/A5089127042","display_name":"Luminita Madalina Marghescu","orcid":null},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Lumini\u0163a M\u0103d\u0103lina Marghescu","raw_affiliation_strings":["Technical University of Cluj-Napoca,Department of Computer Science,Cluj-Napoca,Romania"],"affiliations":[{"raw_affiliation_string":"Technical University of Cluj-Napoca,Department of Computer Science,Cluj-Napoca,Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049230139","display_name":"Rodica Potolea","orcid":"https://orcid.org/0000-0002-7051-3691"},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Rodica Potolea","raw_affiliation_strings":["Technical University of Cluj-Napoca,Department of Computer Science,Cluj-Napoca,Romania"],"affiliations":[{"raw_affiliation_string":"Technical University of Cluj-Napoca,Department of Computer Science,Cluj-Napoca,Romania","institution_ids":["https://openalex.org/I158333966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089127042"],"corresponding_institution_ids":["https://openalex.org/I158333966"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.73381463,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11943","display_name":"Pharmacovigilance and Adverse Drug Reactions","score":0.12210000306367874,"subfield":{"id":"https://openalex.org/subfields/3005","display_name":"Toxicology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11943","display_name":"Pharmacovigilance and Adverse Drug Reactions","score":0.12210000306367874,"subfield":{"id":"https://openalex.org/subfields/3005","display_name":"Toxicology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12268","display_name":"Deception detection and forensic psychology","score":0.10350000113248825,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13192","display_name":"Forensic Fingerprint Detection Methods","score":0.05689999833703041,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.536300003528595},{"id":"https://openalex.org/keywords/adverse-effect","display_name":"Adverse effect","score":0.26969999074935913},{"id":"https://openalex.org/keywords/medline","display_name":"MEDLINE","score":0.24940000474452972},{"id":"https://openalex.org/keywords/risk-assessment","display_name":"Risk assessment","score":0.2483000010251999}],"concepts":[{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.536300003528595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4790000021457672},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3418000042438507},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.28949999809265137},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.28209999203681946},{"id":"https://openalex.org/C197934379","wikidata":"https://www.wikidata.org/wiki/Q2047938","display_name":"Adverse effect","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.24940000474452972},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.2483000010251999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23960000276565552},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22859999537467957}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccp68926.2025.11427139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp68926.2025.11427139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Intelligent Computer Communication and Processing (ICCP)","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":18,"referenced_works":["https://openalex.org/W1934602670","https://openalex.org/W1991154713","https://openalex.org/W2085752173","https://openalex.org/W2163107094","https://openalex.org/W2194506843","https://openalex.org/W2346452181","https://openalex.org/W2911489562","https://openalex.org/W2915623326","https://openalex.org/W4235652147","https://openalex.org/W4378975491","https://openalex.org/W4385308775","https://openalex.org/W4385732850","https://openalex.org/W4389518633","https://openalex.org/W4391577874","https://openalex.org/W4392468106","https://openalex.org/W4399729739","https://openalex.org/W4402670568","https://openalex.org/W4407972356"],"related_works":[],"abstract_inverted_index":{"Adverse":[0,55],"event":[1,125,210,228],"detection":[2],"for":[3,28,130,147,179,206,223],"non-pharmaceutical":[4,113,208],"substances,":[5,114],"such":[6],"as":[7,195],"dietary":[8],"supplements,":[9],"herbal":[10],"remedies,":[11],"and":[12,81,122,166,212,226],"alternative":[13,184],"therapies,":[14],"remains":[15],"a":[16,38,64,70,87,104,203,219],"major":[17],"blind":[18],"spot":[19],"in":[20,234],"current":[21],"pharmacovigilance":[22,188],"systems,":[23],"which":[24],"are":[25],"primarily":[26],"designed":[27],"prescription":[29],"drugs.":[30],"This":[31,134,174,216],"research":[32,142],"addresses":[33],"that":[34,42,111,153],"gap":[35],"by":[36,69,95],"introducing":[37],"high-precision":[39,221],"matching":[40,72,99,157],"framework":[41,222],"links":[43],"scientific":[44],"literature":[45,225],"from":[46,52,116,127],"PubMed":[47,109,119],"with":[48,143],"real-world":[49],"safety":[50],"reports":[51,126],"the":[53,117,128,136,177],"FDA":[54],"Event":[56],"Reporting":[57],"System":[58],"(FAERS).":[59],"The":[60,84],"proposed":[61],"approach":[62],"incorporates":[63],"robust":[65],"pre-processing":[66],"pipeline,":[67],"followed":[68],"threelayer":[71],"engine":[73],"based":[74],"on":[75],"rule-based":[76,156],"substance":[77],"overlap,":[78],"metadata":[79],"alignment,":[80],"temporal":[82],"validation.":[83],"result":[85],"is":[86],"curated":[88],"set":[89],"of":[90,107,183],"560":[91],"article-report":[92,213],"pairs":[93],"obtained":[94],"applying":[96],"our":[97,161],"multi-stage":[98],"pipeline":[100,163],"to":[101],"two":[102],"datasets:":[103],"filtered":[105],"subset":[106],"38,978":[108],"articles":[110],"mention":[112],"drawn":[115],"2024":[118,132],"baseline":[120],"distribution":[121],"135,848":[123],"adverse":[124,145,209,227],"FAERS":[129],"Q3":[131],"(JulySeptember).":[133],"represents":[135],"first":[137,198],"structured":[138],"dataset":[139,175,205],"connecting":[140],"peer-reviewed":[141],"reported":[144],"events":[146],"nonpharmaceutical":[148],"compounds.":[149],"Experimental":[150],"results":[151,191],"show":[152],"while":[154],"raw":[155],"produced":[158],"670":[159],"links,":[160],"enhanced":[162],"reduced":[164],"noise":[165],"improved":[167],"semantic":[168],"accuracy,":[169],"prioritizing":[170],"reliability":[171],"over":[172],"quantity.":[173],"lays":[176],"groundwork":[178],"safer,":[180],"data-driven":[181],"integration":[182],"medicine":[185],"into":[186],"modern":[187],"efforts.":[189],"Moreover,":[190],"so":[192],"far":[193],"serve":[194],"an":[196],"important":[197],"step":[199],"toward":[200],"making":[201],"available":[202],"benchmark":[204],"evaluating":[207],"extraction":[211],"linking":[214,224],"systems.":[215],"work":[217],"provides":[218],"reproducible,":[220],"reports,":[229],"addressing":[230],"challenges":[231],"not":[232],"covered":[233],"prior":[235],"studies.":[236]},"counts_by_year":[],"updated_date":"2026-03-15T07:15:06.534987","created_date":"2026-03-14T00:00:00"}