{"id":"https://openalex.org/W2062652464","doi":"https://doi.org/10.1109/embc.2014.6945177","title":"A cascade classifier for diagnosis of melanoma in clinical images","display_name":"A cascade classifier for diagnosis of melanoma in clinical images","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2062652464","doi":"https://doi.org/10.1109/embc.2014.6945177","mag":"2062652464","pmid":"https://pubmed.ncbi.nlm.nih.gov/25571545"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2014.6945177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2014.6945177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5012151169","display_name":"Pouya Sabouri","orcid":"https://orcid.org/0000-0002-6342-9352"},"institutions":[{"id":"https://openalex.org/I39854758","display_name":"Auckland University of Technology","ror":"https://ror.org/01zvqw119","country_code":"NZ","type":"education","lineage":["https://openalex.org/I39854758"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"P. Sabouri","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland, New Zealand","Auckland University of Technology Department of Electrical and Electronic Engineering Auckland New Zealand"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland, New Zealand","institution_ids":["https://openalex.org/I39854758"]},{"raw_affiliation_string":"Auckland University of Technology Department of Electrical and Electronic Engineering Auckland New Zealand","institution_ids":["https://openalex.org/I39854758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034868132","display_name":"Hamid GholamHosseini","orcid":"https://orcid.org/0000-0002-0135-2687"},"institutions":[{"id":"https://openalex.org/I39854758","display_name":"Auckland University of Technology","ror":"https://ror.org/01zvqw119","country_code":"NZ","type":"education","lineage":["https://openalex.org/I39854758"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"H. GholamHosseini","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Auckland University of Technology, Auckland, New Zealand","Auckland University of Technology, Department of Electrical and Electronics Engineering, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Auckland University of Technology, Auckland, New Zealand","institution_ids":["https://openalex.org/I39854758"]},{"raw_affiliation_string":"Auckland University of Technology, Department of Electrical and Electronics Engineering, Auckland, New Zealand","institution_ids":["https://openalex.org/I39854758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012819592","display_name":"Thomas Larsson","orcid":"https://orcid.org/0000-0002-1550-0994"},"institutions":[{"id":"https://openalex.org/I82509713","display_name":"M\u00e4lardalen University","ror":"https://ror.org/033vfbz75","country_code":"SE","type":"education","lineage":["https://openalex.org/I82509713"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"T. Larsson","raw_affiliation_strings":["M\u00e4lardalen University, V\u00e4ster\u00e5s, Sweden","Malardalen Univ., Va\u0308stera\u0301s, Sweden"],"affiliations":[{"raw_affiliation_string":"M\u00e4lardalen University, V\u00e4ster\u00e5s, Sweden","institution_ids":["https://openalex.org/I82509713"]},{"raw_affiliation_string":"Malardalen Univ., Va\u0308stera\u0301s, Sweden","institution_ids":["https://openalex.org/I82509713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101491500","display_name":"John Collins","orcid":"https://orcid.org/0000-0002-1252-363X"},"institutions":[{"id":"https://openalex.org/I39854758","display_name":"Auckland University of Technology","ror":"https://ror.org/01zvqw119","country_code":"NZ","type":"education","lineage":["https://openalex.org/I39854758"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"J. Collins","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Auckland University of Technology, Auckland, New Zealand","Auckland University of Technology, Department of Electrical and Electronics Engineering, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Auckland University of Technology, Auckland, New Zealand","institution_ids":["https://openalex.org/I39854758"]},{"raw_affiliation_string":"Auckland University of Technology, Department of Electrical and Electronics Engineering, Auckland, New Zealand","institution_ids":["https://openalex.org/I39854758"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5012151169"],"corresponding_institution_ids":["https://openalex.org/I39854758"],"apc_list":null,"apc_paid":null,"fwci":1.0456,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.77233784,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"42","issue":null,"first_page":"6748","last_page":"6751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9983000159263611,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7995519638061523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7167769074440002},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.697234570980072},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6434211730957031},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.583991289138794},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5787667036056519},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5680131316184998},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5380563139915466},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.49241650104522705},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.474552720785141},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4716431498527527},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43855294585227966},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.43396061658859253},{"id":"https://openalex.org/keywords/medical-diagnosis","display_name":"Medical diagnosis","score":0.4322319030761719},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34968364238739014},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3433036804199219},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1259440779685974},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.12586146593093872},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12521794438362122}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7995519638061523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7167769074440002},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.697234570980072},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6434211730957031},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.583991289138794},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5787667036056519},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5680131316184998},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5380563139915466},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.49241650104522705},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.474552720785141},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4716431498527527},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43855294585227966},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.43396061658859253},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.4322319030761719},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34968364238739014},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3433036804199219},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1259440779685974},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.12586146593093872},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12521794438362122},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008545","descriptor_name":"Melanoma","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D008545","descriptor_name":"Melanoma","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D008545","descriptor_name":"Melanoma","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012878","descriptor_name":"Skin Neoplasms","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D012878","descriptor_name":"Skin Neoplasms","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D012878","descriptor_name":"Skin Neoplasms","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055088","descriptor_name":"Early Detection of Cancer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055088","descriptor_name":"Early Detection of Cancer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055088","descriptor_name":"Early Detection of Cancer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2014.6945177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2014.6945177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","raw_type":"proceedings-article"},{"id":"pmid:25571545","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25571545","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1507875776","https://openalex.org/W1976447608","https://openalex.org/W1980347209","https://openalex.org/W1991607872","https://openalex.org/W1991618622","https://openalex.org/W2017743303","https://openalex.org/W2040898244","https://openalex.org/W2051913017","https://openalex.org/W2076586303","https://openalex.org/W2078187356","https://openalex.org/W2087978600","https://openalex.org/W2099397584","https://openalex.org/W2104033477","https://openalex.org/W2133990480","https://openalex.org/W2139888281","https://openalex.org/W2140959850","https://openalex.org/W2150903265","https://openalex.org/W2151153808","https://openalex.org/W2152188843","https://openalex.org/W2153635508"],"related_works":["https://openalex.org/W4367336074","https://openalex.org/W3154045278","https://openalex.org/W4379620016","https://openalex.org/W4393666307","https://openalex.org/W3210764983","https://openalex.org/W4393443811","https://openalex.org/W4367335949","https://openalex.org/W3089416646","https://openalex.org/W4396816114","https://openalex.org/W4380048833"],"abstract_inverted_index":{"Computer":[0],"aided":[1],"diagnosis":[2,14,32],"of":[3,15,25,33,40,64,72,104,108,133,137],"medical":[4,41],"images":[5],"can":[6,110],"help":[7],"physicians":[8],"in":[9,49],"better":[10,120],"detecting":[11],"and":[12,18,45,82,89,106,135],"early":[13],"many":[16],"symptoms":[17],"therefore":[19],"reducing":[20],"the":[21,38,131],"mortality":[22],"rate.":[23],"Realization":[24],"an":[26],"efficient":[27],"mobile":[28],"device":[29],"for":[30,61,92],"semi-automatic":[31],"melanoma":[34,94],"would":[35],"greatly":[36],"enhance":[37],"applicability":[39],"image":[42],"classification":[43,121],"scheme":[44],"make":[46],"it":[47],"useful":[48],"clinical":[50,65],"contexts.":[51],"In":[52,69],"this":[53],"paper,":[54],"interactive":[55],"object":[56],"recognition":[57],"methodology":[58],"is":[59],"adopted":[60],"border":[62],"segmentation":[63],"skin":[66],"lesion":[67],"images.":[68],"addition,":[70],"performance":[71,122],"five":[73],"classifiers,":[74],"KNN,":[75],"Na\u00efve":[76],"Bayes,":[77],"multi-layer":[78],"perceptron,":[79],"random":[80],"forest":[81],"SVM":[83,116],"are":[84],"compared":[85],"based":[86],"on":[87],"color":[88],"texture":[90],"features":[91],"discriminating":[93],"from":[95],"benign":[96],"nevus.":[97],"The":[98],"results":[99],"show":[100],"that":[101],"a":[102,114,119,126],"sensitivity":[103,132],"82.6%":[105],"specificity":[107,136],"83%":[109],"be":[111],"achieved":[112,124],"using":[113,125],"single":[115],"classifier.":[117],"However,":[118],"was":[123],"proposed":[127],"cascade":[128],"classifier":[129],"with":[130],"83.06%":[134],"90.05%":[138],"when":[139],"performing":[140],"ten-fold":[141],"cross":[142],"validation.":[143]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}