{"id":"https://openalex.org/W7123733177","doi":"https://doi.org/10.12720/jait.17.1.1-13","title":"ML and DL Approaches for Drug Review Classification Using a Composite Effectiveness\u2013Satisfaction Score","display_name":"ML and DL Approaches for Drug Review Classification Using a Composite Effectiveness\u2013Satisfaction Score","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7123733177","doi":"https://doi.org/10.12720/jait.17.1.1-13"},"language":"en","primary_location":{"id":"doi:10.12720/jait.17.1.1-13","doi":"https://doi.org/10.12720/jait.17.1.1-13","is_oa":true,"landing_page_url":"https://doi.org/10.12720/jait.17.1.1-13","pdf_url":null,"source":{"id":"https://openalex.org/S136819581","display_name":"Journal of Advances in Information Technology","issn_l":"1798-2340","issn":["1798-2340"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","poland-20","russia-white-list-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Advances in Information Technology","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.12720/jait.17.1.1-13","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5118513821","display_name":"Blessing NWOGU","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Blessing Nwogu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075854906","display_name":"Essia Hamouda","orcid":"https://orcid.org/0000-0002-7281-1860","observed_orcids":["https://orcid.org/0000-0002-7281-1860"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Essia Hamouda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5054139378","display_name":"Khouloud Safi Eljil","orcid":"https://orcid.org/0009-0005-1549-2671","observed_orcids":["https://orcid.org/0009-0005-1549-2671"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khouloud Safi Eljil","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"1","first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9994999766349792,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9994999766349792,"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/T10028","display_name":"Topic Modeling","score":9.999999747378752e-05,"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/T12488","display_name":"Mental Health via Writing","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/patient-generated-content","display_name":"patient-generated content","score":0.8399999737739563},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"sentiment analysis","score":0.8360000252723694},{"id":"https://openalex.org/keywords/user-satisfaction","display_name":"user satisfaction","score":0.4269999861717224},{"id":"https://openalex.org/keywords/bert","display_name":"BERT","score":0.8349999785423279},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.9190000295639038},{"id":"https://openalex.org/keywords/transformer-embeddings","display_name":"transformer embeddings","score":0.527999997138977},{"id":"https://openalex.org/keywords/gloves","display_name":"gloves","score":0.6610000133514404},{"id":"https://openalex.org/keywords/webmd","display_name":"WebMD","score":0.4309999942779541}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5332000255584717},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.48089998960494995},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44110000133514404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4277999997138977},{"id":"https://openalex.org/C104779481","wikidata":"https://www.wikidata.org/wiki/Q50707","display_name":"Composite number","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3580000102519989},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.25459998846054077},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.2526000142097473},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.24729999899864197}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.12720/jait.17.1.1-13","doi":"https://doi.org/10.12720/jait.17.1.1-13","is_oa":true,"landing_page_url":"https://doi.org/10.12720/jait.17.1.1-13","pdf_url":null,"source":{"id":"https://openalex.org/S136819581","display_name":"Journal of Advances in Information Technology","issn_l":"1798-2340","issn":["1798-2340"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","poland-20","russia-white-list-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Advances in Information Technology","raw_type":"journal-article"},{"id":"doi:10.2139/ssrn.5267774","doi":"https://doi.org/10.2139/ssrn.5267774","is_oa":true,"landing_page_url":"https://doi.org/10.2139/ssrn.5267774","pdf_url":null,"source":{"id":"https://openalex.org/S4210172589","display_name":"SSRN Electronic Journal","issn_l":"1556-5068","issn":["1556-5068"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1318003438","host_organization_name":"RELX Group (Netherlands)","host_organization_lineage":["https://openalex.org/I1318003438"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.12720/jait.17.1.1-13","doi":"https://doi.org/10.12720/jait.17.1.1-13","is_oa":true,"landing_page_url":"https://doi.org/10.12720/jait.17.1.1-13","pdf_url":null,"source":{"id":"https://openalex.org/S136819581","display_name":"Journal of Advances in Information Technology","issn_l":"1798-2340","issn":["1798-2340"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","poland-20","russia-white-list-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Advances in Information Technology","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8371999859809875}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2022204871","https://openalex.org/W2036766984","https://openalex.org/W2102742655","https://openalex.org/W2104192042","https://openalex.org/W2250539671","https://openalex.org/W2280199478","https://openalex.org/W2295598076","https://openalex.org/W2547440287","https://openalex.org/W2767716955","https://openalex.org/W2779179495","https://openalex.org/W2792916349","https://openalex.org/W2798859316","https://openalex.org/W2883730939","https://openalex.org/W2896457183","https://openalex.org/W2964056644","https://openalex.org/W2978017171","https://openalex.org/W3094014379","https://openalex.org/W4282830830","https://openalex.org/W4289926728","https://openalex.org/W4366770808","https://openalex.org/W4366829440","https://openalex.org/W4388880998","https://openalex.org/W4396238931","https://openalex.org/W4400659510","https://openalex.org/W4400823820","https://openalex.org/W4405488798","https://openalex.org/W4405584886","https://openalex.org/W4406210188","https://openalex.org/W4406846938"],"related_works":["https://openalex.org/W7117674907","https://openalex.org/W6903736328","https://openalex.org/W4387986235","https://openalex.org/W6885071556","https://openalex.org/W4386921205","https://openalex.org/W7098527077","https://openalex.org/W6960344844","https://openalex.org/W3199766410","https://openalex.org/W3020873116","https://openalex.org/W7203704639"],"abstract_inverted_index":{"With":[0],"the":[1,56,102,132,138,142,152],"increasing":[2],"availability":[3],"of":[4,31,58,66,145,154],"patient-generated":[5],"content":[6],"on":[7,46],"platforms":[8],"like":[9],"WebMD,":[10],"sentiment":[11,161],"analysis":[12,162],"has":[13],"emerged":[14],"as":[15,55],"a":[16,28,47,109],"powerful":[17],"tool":[18],"to":[19,131],"understand":[20],"user":[21],"experiences":[22],"with":[23],"pharmaceuticals.":[24],"This":[25,149],"study":[26],"presents":[27],"comparative":[29],"evaluation":[30],"traditional":[32],"machine":[33],"learning":[34,38],"(ML)":[35],"and":[36,61,73,79,87,94,114,134,141,157,163,172],"deep":[37],"(DL)":[39],"models":[40],"for":[41,159],"classifying":[42],"drug":[43],"reviews":[44],"based":[45],"novel":[48],"composite":[49],"metric-the":[50],"Drug":[51],"Effectiveness-Satisfaction":[52],"Score":[53],"(DESS)-calculated":[54],"average":[57],"user-rated":[59],"effectiveness":[60],"satisfaction.":[62],"A":[63],"diverse":[64],"set":[65],"ML":[67,156],"algorithms":[68],"(Random":[69],"Forest,":[70],"SVM,":[71],"XGBoost)":[72],"DL":[74,158],"architectures":[75],"(LSTM,":[76],"CNN-LSTM,":[77],"DistilBERT,":[78],"BERT)":[80],"were":[81],"tested":[82],"using":[83],"multiple":[84],"feature":[85],"extraction":[86],"embedding":[88],"methods,":[89],"including":[90],"CountVectorizer,":[91],"TF-IDF,":[92],"GloVe,":[93],"transformer-based":[95],"embeddings.":[96],"Results":[97],"show":[98],"that":[99],"BERT":[100],"achieved":[101],"highest":[103],"F1-score":[104],"(87.22%),":[105],"while":[106],"XGBoost":[107],"offered":[108],"strong":[110],"balance":[111],"between":[112],"accuracy":[113],"computational":[115],"efficiency.":[116],"Despite":[117],"robust":[118],"results,":[119],"performance":[120],"was":[121],"slightly":[122],"below":[123],"benchmarks":[124],"reported":[125],"in":[126,167],"other":[127],"domains,":[128],"likely":[129],"due":[130],"complexity":[133],"ambiguity":[135],"introduced":[136],"by":[137],"DESS":[139],"metric":[140],"unstructured":[143],"nature":[144],"real-world":[146],"medical":[147],"reviews.":[148],"work":[150],"underscores":[151],"potential":[153],"combining":[155],"healthcare":[160],"highlights":[164],"future":[165],"opportunities":[166],"domain-specific":[168],"fine-tuning,":[169],"ensemble":[170],"modeling,":[171],"explainable":[173],"AI.":[174]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-01-14T00:00:00"}