{"id":"https://openalex.org/W3090409192","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206603","title":"Double Attention for Pathology Image Diagnosis Network with Visual Interpretability","display_name":"Double Attention for Pathology Image Diagnosis Network with Visual Interpretability","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3090409192","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206603","mag":"3090409192"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5101653791","display_name":"Hao Cheng","orcid":"https://orcid.org/0000-0002-7253-2511"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Cheng","raw_affiliation_strings":["Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053746295","display_name":"Kaijie Wu","orcid":"https://orcid.org/0000-0003-4350-8878"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaijie Wu","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100621577","display_name":"Kai Ma","orcid":"https://orcid.org/0000-0003-2805-3692"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Ma","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072119654","display_name":"Jie Tian","orcid":"https://orcid.org/0000-0002-4845-5085"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tian","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101888899","display_name":"Rui Xu","orcid":"https://orcid.org/0000-0002-5549-236X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Xu","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030921410","display_name":"Chaochen Gu","orcid":"https://orcid.org/0000-0002-9748-7139"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaochen Gu","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100690710","display_name":"Xinping Guan","orcid":"https://orcid.org/0009-0006-6233-8762"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinping Guan","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101653791"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.549891,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"542","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9993000030517578,"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/T10862","display_name":"AI in cancer detection","score":0.9993000030517578,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10146","display_name":"Cervical Cancer and HPV Research","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/interpretability","display_name":"Interpretability","score":0.900348961353302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7162563800811768},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6903499364852905},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6385401487350464},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4494473934173584},{"id":"https://openalex.org/keywords/cervical-cancer","display_name":"Cervical cancer","score":0.449446439743042},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44276684522628784},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44015079736709595},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4263031780719757},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.2519086003303528},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.19950392842292786}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.900348961353302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7162563800811768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6903499364852905},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6385401487350464},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4494473934173584},{"id":"https://openalex.org/C2778220009","wikidata":"https://www.wikidata.org/wiki/Q160105","display_name":"Cervical cancer","level":3,"score":0.449446439743042},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44276684522628784},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44015079736709595},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4263031780719757},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.2519086003303528},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.19950392842292786},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6100000143051147,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W22040386","https://openalex.org/W1514535095","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1937937026","https://openalex.org/W2001810343","https://openalex.org/W2027423900","https://openalex.org/W2117539524","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2317125622","https://openalex.org/W2334763311","https://openalex.org/W2546696630","https://openalex.org/W2560645892","https://openalex.org/W2575842049","https://openalex.org/W2581082771","https://openalex.org/W2585922243","https://openalex.org/W2724276442","https://openalex.org/W2735683533","https://openalex.org/W2752895231","https://openalex.org/W2767236661","https://openalex.org/W2901236971","https://openalex.org/W2950178297","https://openalex.org/W2950489286","https://openalex.org/W2952469094","https://openalex.org/W2963075078","https://openalex.org/W2963300078","https://openalex.org/W2963409068","https://openalex.org/W2963446712","https://openalex.org/W2963745697","https://openalex.org/W2963967185","https://openalex.org/W3098325931","https://openalex.org/W6630875275","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6684191040","https://openalex.org/W6687483927","https://openalex.org/W6725207838","https://openalex.org/W6729399837","https://openalex.org/W6731895421","https://openalex.org/W6784955093"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"cervical":[3,20,27,153],"cancer":[4],"has":[5],"been":[6],"one":[7],"of":[8,19,50,69,91],"the":[9,44,87,92,107,110,119,127,164],"most":[10],"common":[11],"diseases":[12],"in":[13,140],"women's":[14],"cancer.":[15,28],"The":[16,136],"advanced":[17],"diagnosis":[18,63,85],"precancerous":[21],"lesions":[22],"is":[23,138],"essential":[24],"for":[25,65,147],"preventing":[26],"Its":[29],"effectiveness":[30,88],"and":[31,47,79,89,132,159],"efficiency":[32,90],"can":[33],"be":[34],"greatly":[35],"improved":[36],"by":[37,43,125],"computer":[38],"aided":[39,84],"diagnosis,":[40],"while":[41],"challenged":[42],"imprecise":[45],"conclusions":[46],"uninterpretable":[48],"process":[49],"diagnosis.":[51],"To":[52],"solve":[53],"this":[54],"problem,":[55],"we":[56],"propose":[57],"a":[58,80,97,168,175],"novel":[59],"deep":[60],"learning-based":[61],"interpretable":[62],"system":[64],"pathology":[66],"images,":[67,156],"consisting":[68],"three":[70],"interrelated":[71],"models:":[72],"an":[73,76,141],"image":[74,94],"model,":[75,114],"attention":[77,113],"model":[78,95,108],"conclusion":[81,128],"model.":[82,149],"Computer":[83],"improves":[86],"proposed":[93,165],"uses":[96],"convolutional":[98],"neural":[99],"network":[100,137],"(CNN)":[101],"to":[102,117],"ex-tract":[103],"semantic":[104,111],"features.":[105],"Combining":[106],"with":[109,144,174],"attribute":[112],"it":[115],"aims":[116],"capture":[118],"discriminant":[120],"relationship":[121],"between":[122],"se-mantic":[123],"attributes":[124],"predicting":[126],"label":[129,160],"through":[130],"long-term":[131],"short-term":[133],"memory":[134],"(LSTM).":[135],"trained":[139],"end-to-end":[142],"manner,":[143],"different":[145],"weights":[146],"each":[148],"Experimental":[150],"results":[151],"on":[152],"intraepithelial":[154],"neoplasia":[155],"diagnostic":[157],"reports":[158],"datasets":[161],"show":[162],"that":[163],"method":[166],"achieves":[167],"significant":[169],"improvement":[170],"over":[171],"traditional":[172],"methods":[173],"better":[176],"interpretability.":[177]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
