{"id":"https://openalex.org/W2986279317","doi":"https://doi.org/10.1166/jmihi.2020.2967","title":"Deep Transfer Learning for Histopathological Diagnosis of Cervical Cancer Using Convolutional Neural Networks with Visualization Schemes","display_name":"Deep Transfer Learning for Histopathological Diagnosis of Cervical Cancer Using Convolutional Neural Networks with Visualization Schemes","publication_year":2019,"publication_date":"2019-11-12","ids":{"openalex":"https://openalex.org/W2986279317","doi":"https://doi.org/10.1166/jmihi.2020.2967","mag":"2986279317"},"language":"en","primary_location":{"id":"doi:10.1166/jmihi.2020.2967","is_oa":false,"landing_page_url":"https://doi.org/10.1166/jmihi.2020.2967","pdf_url":null,"source":{"id":"https://openalex.org/S2502047498","display_name":"Journal of Medical Imaging and Health Informatics","issn_l":"2156-7018","issn":["2156-7018","2156-7026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310321646","host_organization_name":"American Scientific Publishers","host_organization_lineage":["https://openalex.org/P4310321646"],"host_organization_lineage_names":["American Scientific Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Medical Imaging and Health Informatics","raw_type":"journal-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/A5027016896","display_name":"Ying Chen","orcid":"https://orcid.org/0000-0002-1914-8780"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ying Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109938867","display_name":"Xiaomin Qin","orcid":"https://orcid.org/0000-0002-3411-444X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaomin Qin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063795066","display_name":"Jingyu Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jingyu Xiong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084521046","display_name":"Shugong Xu","orcid":"https://orcid.org/0000-0003-1905-6269"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shugong Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088526370","display_name":"Jun Shi","orcid":"https://orcid.org/0000-0003-4520-8975"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Shi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059749075","display_name":"Huabing Lv","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huabing Lv","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412927","display_name":"Lin Li","orcid":"https://orcid.org/0000-0003-0754-8143"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031257969","display_name":"Hui Xing","orcid":"https://orcid.org/0000-0002-1631-1167"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hui Xing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100360194","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0001-5303-9804"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Zhang","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":0.8471,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.80864253,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"10","issue":"2","first_page":"391","last_page":"400"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9994000196456909,"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":0.9994000196456909,"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/T10146","display_name":"Cervical Cancer and HPV Research","score":0.9948999881744385,"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"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9696000218391418,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.817112922668457},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8088663816452026},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6789103150367737},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6345313787460327},{"id":"https://openalex.org/keywords/cervical-cancer","display_name":"Cervical cancer","score":0.630550742149353},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5829582810401917},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5480998158454895},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5286672115325928},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49375924468040466},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38332316279411316},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.30548402667045593},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.27346354722976685},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.061676025390625}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.817112922668457},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8088663816452026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6789103150367737},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6345313787460327},{"id":"https://openalex.org/C2778220009","wikidata":"https://www.wikidata.org/wiki/Q160105","display_name":"Cervical cancer","level":3,"score":0.630550742149353},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5829582810401917},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5480998158454895},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5286672115325928},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49375924468040466},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38332316279411316},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.30548402667045593},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.27346354722976685},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.061676025390625}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1166/jmihi.2020.2967","is_oa":false,"landing_page_url":"https://doi.org/10.1166/jmihi.2020.2967","pdf_url":null,"source":{"id":"https://openalex.org/S2502047498","display_name":"Journal of Medical Imaging and Health Informatics","issn_l":"2156-7018","issn":["2156-7018","2156-7026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310321646","host_organization_name":"American Scientific Publishers","host_organization_lineage":["https://openalex.org/P4310321646"],"host_organization_lineage_names":["American Scientific Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Medical Imaging and Health Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W3183901164","https://openalex.org/W2951211570","https://openalex.org/W3176438653","https://openalex.org/W3135818718","https://openalex.org/W4290188444","https://openalex.org/W3167935049","https://openalex.org/W3003905048","https://openalex.org/W2253429366","https://openalex.org/W3127975138"],"abstract_inverted_index":{"This":[0],"study":[1],"aimed":[2],"to":[3,24,39,100],"propose":[4],"a":[5,113],"deep":[6],"transfer":[7,45],"learning":[8,46,78],"framework":[9],"for":[10,28,47,160,179],"histopathological":[11,50,69,180],"image":[12,61],"analysis":[13],"by":[14],"using":[15],"convolutional":[16,89],"neural":[17],"networks":[18],"(CNNs)":[19],"with":[20],"visualization":[21],"schemes,":[22],"and":[23,30,63,93,122,142,164,169],"evaluate":[25],"its":[26],"usage":[27],"automated":[29],"interpretable":[31],"diagnosis":[32,181],"of":[33,43,76,91,96,105,115,182],"cervical":[34,117,161,183],"cancer.":[35,184],"First,":[36],"in":[37,176],"order":[38],"examine":[40],"the":[41,44,74,87,94,102,106,146,155],"potential":[42],"classifying":[48],"cervix":[49],"images,":[51],"we":[52,72,84],"pre-trained":[53],"three":[54,77],"state-of-the-art":[55],"CNN":[56],"architectures":[57],"on":[58,67,80,112,158],"large-size":[59],"natural":[60],"datasets":[62],"then":[64],"fine-tuned":[65],"them":[66],"small-size":[68],"datasets.":[70],"Second,":[71],"investigated":[73],"impact":[75],"strategies":[79],"classification":[81,163],"accuracy.":[82,170],"Third,":[83],"visualized":[85],"both":[86],"multiple-layer":[88],"kernels":[90],"CNNs":[92],"regions":[95],"interest":[97],"so":[98],"as":[99],"increase":[101],"clinical":[103,177],"interpretability":[104],"networks.":[107],"Our":[108,151],"method":[109,131,152],"was":[110],"evaluated":[111],"database":[114],"4993":[116],"histological":[118],"images":[119],"(2503":[120],"benign":[121],"2490":[123],"malignant).":[124],"The":[125],"experimental":[126],"results":[127],"demonstrated":[128],"that":[129],"our":[130],"achieved":[132],"95.88%":[133],"sensitivity,":[134],"98.93%":[135],"specificity,":[136],"97.42%":[137],"accuracy,":[138],"94.81%":[139],"Youden's":[140],"index":[141],"99.71%":[143],"area":[144],"under":[145],"receiver":[147],"operating":[148],"characteristic":[149],"curve.":[150],"can":[153],"reduce":[154],"cognitive":[156],"burden":[157],"pathologists":[159],"disease":[162],"improve":[165],"their":[166],"diagnostic":[167],"efficiency":[168],"It":[171],"may":[172],"be":[173],"potentially":[174],"used":[175],"routine":[178]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}