{"id":"https://openalex.org/W3082318197","doi":"https://doi.org/10.1145/3411408.3411461","title":"Drug-Drug Interaction Classification Using Attention Based Neural Networks","display_name":"Drug-Drug Interaction Classification Using Attention Based Neural Networks","publication_year":2020,"publication_date":"2020-09-01","ids":{"openalex":"https://openalex.org/W3082318197","doi":"https://doi.org/10.1145/3411408.3411461","mag":"3082318197"},"language":"en","primary_location":{"id":"doi:10.1145/3411408.3411461","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3411408.3411461","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"11th Hellenic Conference on Artificial Intelligence","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/A5014901230","display_name":"Dimitrios Zaikis","orcid":"https://orcid.org/0000-0002-0361-7060"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Dimitrios Zaikis","raw_affiliation_strings":["Aristotle University of Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066340205","display_name":"Ioannis Vlahavas","orcid":"https://orcid.org/0000-0003-3477-8825"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioannis Vlahavas","raw_affiliation_strings":["Aristotle University of Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014901230"],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":0.1657,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.49810637,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"34","last_page":"40"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9804999828338623,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7579541206359863},{"id":"https://openalex.org/keywords/drug-repositioning","display_name":"Drug repositioning","score":0.6622179746627808},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6470147371292114},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6435104608535767},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6089922189712524},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.5953298807144165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5761365294456482},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5372284650802612},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5103601813316345},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5044659376144409},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4725249409675598},{"id":"https://openalex.org/keywords/drug-drug-interaction","display_name":"Drug-drug interaction","score":0.4527556598186493},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44927841424942017},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.11852598190307617},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.07873344421386719}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7579541206359863},{"id":"https://openalex.org/C103637391","wikidata":"https://www.wikidata.org/wiki/Q5308921","display_name":"Drug repositioning","level":3,"score":0.6622179746627808},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6470147371292114},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6435104608535767},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6089922189712524},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.5953298807144165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5761365294456482},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5372284650802612},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5103601813316345},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5044659376144409},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4725249409675598},{"id":"https://openalex.org/C2910466267","wikidata":"https://www.wikidata.org/wiki/Q718753","display_name":"Drug-drug interaction","level":3,"score":0.4527556598186493},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44927841424942017},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.11852598190307617},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.07873344421386719},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3411408.3411461","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3411408.3411461","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"11th Hellenic Conference on Artificial Intelligence","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/W179875071","https://openalex.org/W1850865022","https://openalex.org/W2060515712","https://openalex.org/W2114361266","https://openalex.org/W2148488766","https://openalex.org/W2170189740","https://openalex.org/W2171928131","https://openalex.org/W2295030615","https://openalex.org/W2612649659","https://openalex.org/W2741951152","https://openalex.org/W2765742249","https://openalex.org/W2890830728","https://openalex.org/W2911489562","https://openalex.org/W2963923670","https://openalex.org/W2964167098","https://openalex.org/W3004541293","https://openalex.org/W3019826089","https://openalex.org/W3105491236"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W4281673370","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4206422705","https://openalex.org/W1980001478"],"abstract_inverted_index":{"Drug-drug":[0],"interaction":[1],"(DDI)":[2],"identification":[3],"is":[4],"the":[5,28,67,85,123,129,137,149,153],"task":[6,126],"of":[7,98,147,152,166],"identifying":[8],"potential":[9],"interactions":[10,17],"between":[11,87],"drugs":[12],"when":[13],"administered":[14],"simultaneously.":[15],"The":[16],"can":[18,26,37,162],"be":[19],"synergetic":[20],"or":[21],"antagonistic":[22,35],"as":[23],"one":[24],"drug":[25,31,130,134],"affect":[27],"other.":[29],"Adverse":[30],"reactions":[32],"caused":[33],"by":[34],"DDI":[36,58,124],"pose":[38],"a":[39,94,169],"serious":[40],"threat":[41],"to":[42,47,63,81,121,142],"health":[43,51],"and":[44,83,106,117,127,133],"potentially":[45],"lead":[46],"greater":[48],"increase":[49,69],"in":[50,70],"care":[52],"expenditure.":[53],"Multiple":[54],"excellent":[55],"resources":[56],"for":[57],"already":[59],"exist,":[60],"although":[61],"unable":[62],"keep":[64],"up":[65],"with":[66,168],"exponential":[68],"published":[71],"biomedical":[72],"literature.":[73],"Most":[74],"existing":[75],"systems":[76],"rely":[77],"on":[78,145],"handcrafted":[79],"features":[80],"extract":[82],"classify":[84],"relationships":[86],"drugs.":[88],"In":[89],"this":[90],"paper,":[91],"we":[92],"present":[93],"deep":[95],"learning":[96],"method":[97,161],"stacked":[99],"bidirectional":[100],"Long":[101],"Short":[102],"Term":[103],"Memory":[104],"(Bi-LSTM)":[105],"Convolutional":[107],"neural":[108],"(CNN)":[109],"networks":[110],"that":[111,159],"utilize":[112],"word":[113],"embeddings,":[114],"part-of-speech":[115],"tags":[116],"distance":[118],"embeddings":[119],"respectively":[120],"perform":[122],"extraction":[125],"aid":[128],"development":[131],"cycle":[132],"repurposing.":[135],"Furthermore,":[136],"model":[138],"uses":[139],"attention":[140],"mechanism":[141],"better":[143,163],"focus":[144],"importance":[146],"all":[148],"hidden":[150],"states":[151],"Bi-LSTM":[154],"layers.":[155],"Experimental":[156],"results":[157],"show":[158],"our":[160],"avoid":[164],"misclassifications":[165],"instances":[167],"minimal":[170],"preprocessing.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3},{"year":2022,"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"}
