{"id":"https://openalex.org/W3012494997","doi":"https://doi.org/10.1109/ccwc47524.2020.9031163","title":"Prediction of Cancer Drug Effectiveness Based on Multi-Fusion Deep Learning Model","display_name":"Prediction of Cancer Drug Effectiveness Based on Multi-Fusion Deep Learning Model","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3012494997","doi":"https://doi.org/10.1109/ccwc47524.2020.9031163","mag":"3012494997"},"language":"en","primary_location":{"id":"doi:10.1109/ccwc47524.2020.9031163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc47524.2020.9031163","pdf_url":null,"source":{"id":"https://openalex.org/S4306498584","display_name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100340665","display_name":"Qian Li","orcid":"https://orcid.org/0000-0003-3240-8871"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Li","raw_affiliation_strings":["School of software, TongJi University, ShangHai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of software, TongJi University, ShangHai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029236040","display_name":"Jie Huang","orcid":"https://orcid.org/0000-0002-7684-2533"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Huang","raw_affiliation_strings":["School of software, TongJi University, ShangHai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of software, TongJi University, ShangHai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030414508","display_name":"Hongming Zhu","orcid":"https://orcid.org/0000-0001-5795-5279"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"HongMing Zhu","raw_affiliation_strings":["School of software, TongJi University, ShangHai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of software, TongJi University, ShangHai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026465152","display_name":"Qin Liu","orcid":"https://orcid.org/0000-0002-9352-1694"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin Liu","raw_affiliation_strings":["School of software, Tsingtao Advanced Research Institute, TongJi University, ShangHai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of software, Tsingtao Advanced Research Institute, TongJi University, ShangHai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":null,"first_page":"0634","last_page":"0639"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9998000264167786,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9828000068664551,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials 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":0.7439788579940796},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.726565420627594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6911654472351074},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6459268927574158},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6116642355918884},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.563970685005188},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.5336222052574158},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.5051954388618469},{"id":"https://openalex.org/keywords/premise","display_name":"Premise","score":0.5033184885978699},{"id":"https://openalex.org/keywords/precision-medicine","display_name":"Precision medicine","score":0.48746562004089355},{"id":"https://openalex.org/keywords/drug-response","display_name":"Drug response","score":0.4445716142654419},{"id":"https://openalex.org/keywords/drug-target","display_name":"Drug target","score":0.43988481163978577},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1322818398475647},{"id":"https://openalex.org/keywords/cancer-research","display_name":"Cancer research","score":0.10421255230903625},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.09877589344978333},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08073887228965759}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7439788579940796},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.726565420627594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6911654472351074},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6459268927574158},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6116642355918884},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.563970685005188},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.5336222052574158},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.5051954388618469},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.5033184885978699},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.48746562004089355},{"id":"https://openalex.org/C2994119904","wikidata":"https://www.wikidata.org/wiki/Q1251001","display_name":"Drug response","level":3,"score":0.4445716142654419},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.43988481163978577},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1322818398475647},{"id":"https://openalex.org/C502942594","wikidata":"https://www.wikidata.org/wiki/Q3421914","display_name":"Cancer research","level":1,"score":0.10421255230903625},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.09877589344978333},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08073887228965759},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C548081761","wikidata":"https://www.wikidata.org/wiki/Q180388","display_name":"Waste management","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccwc47524.2020.9031163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc47524.2020.9031163","pdf_url":null,"source":{"id":"https://openalex.org/S4306498584","display_name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W108176572","https://openalex.org/W1872239493","https://openalex.org/W2018663224","https://openalex.org/W2024800283","https://openalex.org/W2058299802","https://openalex.org/W2073295808","https://openalex.org/W2097561421","https://openalex.org/W2108068107","https://openalex.org/W2113847750","https://openalex.org/W2120204563","https://openalex.org/W2128374258","https://openalex.org/W2129860849","https://openalex.org/W2137297899","https://openalex.org/W2139602588","https://openalex.org/W2148895006","https://openalex.org/W2152883907","https://openalex.org/W2159851582","https://openalex.org/W2159887157","https://openalex.org/W2177317049","https://openalex.org/W2329659234","https://openalex.org/W2418269856","https://openalex.org/W2533800772","https://openalex.org/W2546885909","https://openalex.org/W2587828787","https://openalex.org/W2753588101","https://openalex.org/W2757960269","https://openalex.org/W2768148056","https://openalex.org/W2778455075","https://openalex.org/W2790808809","https://openalex.org/W2794284562","https://openalex.org/W2807463161","https://openalex.org/W2901218091","https://openalex.org/W2912552806","https://openalex.org/W2963046727","https://openalex.org/W6717268982","https://openalex.org/W6747530153"],"related_works":["https://openalex.org/W590788508","https://openalex.org/W4235873430","https://openalex.org/W2611974471","https://openalex.org/W4313233093","https://openalex.org/W2358082531","https://openalex.org/W2589976903","https://openalex.org/W2335596023","https://openalex.org/W2026719400","https://openalex.org/W2374273535","https://openalex.org/W2159063798"],"abstract_inverted_index":{"Oncogenomics":[0],"is":[1,30],"the":[2,10,23,37,58,68,93,99,104,108,113,118,123,127,156,176,183,212],"premise":[3],"of":[4,14,25,39,50,60,103,112,126,178,193,214],"precision":[5],"medicine,":[6],"which":[7],"has":[8],"attracted":[9],"attention":[11],"and":[12,70,73,107,115,129,146,207],"research":[13],"many":[15],"scholars":[16],"in":[17,52,175],"recent":[18],"years.":[19],"Among":[20],"them,":[21],"predicting":[22],"response":[24,38,136,205],"cell":[26,40,105],"lines":[27,41],"to":[28,42,97,186],"drugs":[29,43,62],"a":[31,48,81,167,171,190,200],"very":[32],"important":[33],"topic.":[34],"Because":[35],"understanding":[36],"can":[44,154],"not":[45],"only":[46],"save":[47],"lot":[49],"time":[51],"drug":[53,135,169,204],"screening,":[54],"but":[55],"also":[56],"promote":[57],"reuse":[59],"existing":[61],"that":[63,151],"have":[64],"been":[65],"approved":[66],"by":[67],"Food":[69],"Drug":[71],"Administration(FDA)":[72],"other":[74],"regulatory":[75],"agencies.":[76],"Herein,":[77],"this":[78,88,179],"paper":[79,198],"proposed":[80],"new":[82,201],"multi-fusion":[83],"neural":[84,132],"network":[85],"model.":[86],"In":[87,159],"model,":[89,148,180],"we":[90,149,181],"first":[91],"use":[92,117],"Convolutional":[94],"Neural":[95],"Network(CNN)":[96],"capture":[98],"gene":[100],"expression":[101],"features":[102,111,121],"line":[106],"molecular":[109],"descriptor":[110],"drug,":[114],"then":[116],"resulting":[119],"abstract":[120],"as":[122],"input":[124],"data":[125],"long":[128],"short-term":[130],"memory":[131],"network(LSTM)":[133],"for":[134,203,211],"prediction.":[137],"By":[138],"comparison":[139],"with":[140,162],"some":[141,209],"traditional":[142],"machine":[143],"learning":[144],"algorithms":[145],"CNN":[147],"found":[150],"our":[152],"model":[153],"improve":[155],"prediction":[157,206],"accuracy.":[158],"addition,":[160],"compared":[161],"previous":[163],"works":[164],"on":[165],"modeling":[166],"single":[168,172],"or":[170],"cancer":[173],"type,":[174],"design":[177],"extended":[182],"application":[184],"categories":[185],"human":[187],"tissues,":[188],"where":[189],"tissue":[191],"consists":[192],"multiple":[194],"TCGA":[195],"types.":[196],"This":[197],"provides":[199,208],"method":[202],"guidance":[210],"screening":[213],"effective":[215],"anti-cancer":[216],"drug.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}