{"id":"https://openalex.org/W4285152660","doi":"https://doi.org/10.1109/access.2022.3181225","title":"FixCaps: An Improved Capsules Network for Diagnosis of Skin Cancer","display_name":"FixCaps: An Improved Capsules Network for Diagnosis of Skin Cancer","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285152660","doi":"https://doi.org/10.1109/access.2022.3181225"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3181225","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3181225","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9791217/09791221.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9791217/09791221.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035034944","display_name":"Zhangli Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I63371133","display_name":"Chongqing Jiaotong University","ror":"https://ror.org/01t001k65","country_code":"CN","type":"education","lineage":["https://openalex.org/I63371133"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhangli Lan","raw_affiliation_strings":["Chongqing Jiaotong University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing Jiaotong University, Chongqing, China","institution_ids":["https://openalex.org/I63371133"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027872942","display_name":"Songbai Cai","orcid":"https://orcid.org/0000-0002-2836-360X"},"institutions":[{"id":"https://openalex.org/I63371133","display_name":"Chongqing Jiaotong University","ror":"https://ror.org/01t001k65","country_code":"CN","type":"education","lineage":["https://openalex.org/I63371133"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songbai Cai","raw_affiliation_strings":["Chongqing Jiaotong University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing Jiaotong University, Chongqing, China","institution_ids":["https://openalex.org/I63371133"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023714516","display_name":"Xu He","orcid":"https://orcid.org/0000-0002-7129-8006"},"institutions":[{"id":"https://openalex.org/I63371133","display_name":"Chongqing Jiaotong University","ror":"https://ror.org/01t001k65","country_code":"CN","type":"education","lineage":["https://openalex.org/I63371133"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu He","raw_affiliation_strings":["Chongqing Jiaotong University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing Jiaotong University, Chongqing, China","institution_ids":["https://openalex.org/I63371133"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043857276","display_name":"Xinpeng Wen","orcid":"https://orcid.org/0009-0000-9419-0252"},"institutions":[{"id":"https://openalex.org/I63371133","display_name":"Chongqing Jiaotong University","ror":"https://ror.org/01t001k65","country_code":"CN","type":"education","lineage":["https://openalex.org/I63371133"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinpeng Wen","raw_affiliation_strings":["Chongqing Jiaotong University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing Jiaotong University, Chongqing, China","institution_ids":["https://openalex.org/I63371133"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5035034944"],"corresponding_institution_ids":["https://openalex.org/I63371133"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.9058,"has_fulltext":true,"cited_by_count":70,"citation_normalized_percentile":{"value":0.97954886,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"10","issue":null,"first_page":"76261","last_page":"76267"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10862","display_name":"AI in cancer detection","score":0.9952999949455261,"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/T11306","display_name":"Nonmelanoma Skin Cancer Studies","score":0.9919999837875366,"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/kernel","display_name":"Kernel (algebra)","score":0.712531328201294},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7098754644393921},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6573910713195801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6355951428413391},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6305645108222961},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.618043839931488},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5682578682899475},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.51374351978302},{"id":"https://openalex.org/keywords/skin-cancer","display_name":"Skin cancer","score":0.5043133497238159},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4143470525741577},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4108010530471802},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3184746205806732},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.2183527946472168},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20113947987556458},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1811113953590393},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1256004273891449}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.712531328201294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7098754644393921},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6573910713195801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6355951428413391},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6305645108222961},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.618043839931488},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5682578682899475},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.51374351978302},{"id":"https://openalex.org/C2777789703","wikidata":"https://www.wikidata.org/wiki/Q192102","display_name":"Skin cancer","level":3,"score":0.5043133497238159},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4143470525741577},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4108010530471802},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3184746205806732},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.2183527946472168},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20113947987556458},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1811113953590393},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1256004273891449},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2022.3181225","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3181225","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9791217/09791221.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:91f67534d51e470eb83d459f331c4092","is_oa":true,"landing_page_url":"https://doaj.org/article/91f67534d51e470eb83d459f331c4092","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 76261-76267 (2022)","raw_type":"article"},{"id":"pmh:oai:zenodo.org:7141660","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ACCESS.2022.3181225","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, 10, 76261-76267, (2022-06-08)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3181225","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3181225","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9791217/09791221.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285152660.pdf","grobid_xml":"https://content.openalex.org/works/W4285152660.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W77200240","https://openalex.org/W1966570239","https://openalex.org/W2095705004","https://openalex.org/W2112796928","https://openalex.org/W2194775991","https://openalex.org/W2426942631","https://openalex.org/W2794825826","https://openalex.org/W2884585870","https://openalex.org/W2895526696","https://openalex.org/W2919115771","https://openalex.org/W2963384288","https://openalex.org/W2963946669","https://openalex.org/W2964350391","https://openalex.org/W2965481041","https://openalex.org/W2982083293","https://openalex.org/W3022365663","https://openalex.org/W3097337942","https://openalex.org/W3097588203","https://openalex.org/W3102785203","https://openalex.org/W3118608800","https://openalex.org/W3119766921","https://openalex.org/W3192610404","https://openalex.org/W3204882321","https://openalex.org/W4206841660","https://openalex.org/W4211038303","https://openalex.org/W4225845169","https://openalex.org/W4246193833","https://openalex.org/W6637373629","https://openalex.org/W6638444622","https://openalex.org/W6674330103","https://openalex.org/W6679852000","https://openalex.org/W6684191040","https://openalex.org/W6703892329","https://openalex.org/W6743446608","https://openalex.org/W6743688258","https://openalex.org/W6747050675","https://openalex.org/W6748053814","https://openalex.org/W6761152059","https://openalex.org/W6766394743","https://openalex.org/W6787972765","https://openalex.org/W6903718765"],"related_works":["https://openalex.org/W3034421924","https://openalex.org/W2982536526","https://openalex.org/W4386858688","https://openalex.org/W4380302312","https://openalex.org/W3008689640","https://openalex.org/W2748667022","https://openalex.org/W4390971171","https://openalex.org/W4385338604","https://openalex.org/W3081626085","https://openalex.org/W3211770882"],"abstract_inverted_index":{"The":[0,113,132,145,164],"early":[1,20],"detection":[2,150],"of":[3,12,34,60,124,157,177,185],"skin":[4,24,51],"cancer":[5,52],"substantially":[6],"improves":[7],"the":[8,91,122,142,149,188],"five-year":[9],"survival":[10],"rate":[11],"patients.":[13],"It":[14],"is":[15,98,170,181],"often":[16,55],"difficult":[17],"to":[18,45,107,120,137],"distinguish":[19],"malignant":[21],"tumors":[22],"from":[23],"images,":[25,179],"even":[26],"by":[27,84,128],"expert":[28],"dermatologists.":[29],"Therefore,":[30],"several":[31,161],"classification":[32,175],"methods":[33],"dermatoscopic":[35,178],"images":[36],"have":[37,42],"been":[38,43],"proposed,":[39],"but":[40],"they":[41],"found":[44],"be":[46],"inadequate":[47],"or":[48],"defective":[49],"for":[50,71],"detection,":[53],"and":[54,130,152],"require":[56],"a":[57,78,154],"large":[58,100],"amount":[59,156],"calculations.":[61],"This":[62],"study":[63],"proposes":[64],"an":[65,86,183],"improved":[66],"capsule":[67,143],"network":[68,146],"called":[69],"FixCaps":[70,75,169],"dermoscopic":[72],"image":[73],"classification.":[74],"can":[76,147],"obtain":[77],"larger":[79],"receptive":[80],"field":[81],"than":[82,172],"CapsNets":[83],"applying":[85],"efficient":[87],"high-performance":[88],"large-kernel":[89],"at":[90],"bottom":[92],"convolution":[93,129,134],"layer":[94],"whose":[95],"kernel":[96],"size":[97],"as":[99,101],"31":[102],"&#x00D7;":[103,111],"31,":[104],"in":[105,141,174],"contrast":[106],"commonly":[108],"used":[109,119,136],"9":[110],"9.":[112],"convolutional":[114],"block":[115],"attention":[116],"module":[117],"was":[118,135],"reduce":[121,153],"losses":[123],"spatial":[125],"information":[126],"caused":[127],"pooling.":[131],"group":[133],"avoid":[138],"model":[139],"underfitting":[140],"layer.":[144],"improve":[148],"accuracy":[151,184],"great":[155],"calculations,":[158],"compared":[159],"with":[160],"existing":[162],"methods.":[163],"experimental":[165],"results":[166],"showed":[167],"that":[168],"better":[171],"IRv2-SA":[173],"prediction":[176],"which":[180],"achieved":[182],"96.49%":[186],"on":[187],"HAM10000":[189],"dataset.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-30T08:08:38.191290","created_date":"2025-10-10T00:00:00"}
