{"id":"https://openalex.org/W3000746448","doi":"https://doi.org/10.1109/iccp48234.2019.8959661","title":"Skin Lesion Diagnosis Using Deep Learning","display_name":"Skin Lesion Diagnosis Using Deep Learning","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W3000746448","doi":"https://doi.org/10.1109/iccp48234.2019.8959661","mag":"3000746448"},"language":"en","primary_location":{"id":"doi:10.1109/iccp48234.2019.8959661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp48234.2019.8959661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP)","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/A5037086480","display_name":"Horea-Bogdan Muresan","orcid":null},"institutions":[{"id":"https://openalex.org/I3125347698","display_name":"Babe\u0219-Bolyai University","ror":"https://ror.org/02rmd1t30","country_code":"RO","type":"education","lineage":["https://openalex.org/I3125347698"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Horea-Bogdan Mure\u015fan","raw_affiliation_strings":["Babe&#x015F;-Bolyai University,Faculty of Mathematics and Computer Science,Romania","Faculty of Mathematics and Computer Science, Babe\u015f-Bolyai University, Romania"],"affiliations":[{"raw_affiliation_string":"Babe&#x015F;-Bolyai University,Faculty of Mathematics and Computer Science,Romania","institution_ids":["https://openalex.org/I3125347698"]},{"raw_affiliation_string":"Faculty of Mathematics and Computer Science, Babe\u015f-Bolyai University, Romania","institution_ids":["https://openalex.org/I3125347698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5037086480"],"corresponding_institution_ids":["https://openalex.org/I3125347698"],"apc_list":null,"apc_paid":null,"fwci":0.3022,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.64014912,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"499","last_page":"506"},"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":0.9865000247955322,"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":0.9765999913215637,"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/computer-science","display_name":"Computer science","score":0.801855206489563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7154457569122314},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6855744123458862},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.659285843372345},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.6020686626434326},{"id":"https://openalex.org/keywords/skin-lesion","display_name":"Skin lesion","score":0.5407083630561829},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.5336334109306335},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4174519181251526},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.08477035164833069}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.801855206489563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7154457569122314},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6855744123458862},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.659285843372345},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.6020686626434326},{"id":"https://openalex.org/C2988168687","wikidata":"https://www.wikidata.org/wiki/Q949302","display_name":"Skin lesion","level":2,"score":0.5407083630561829},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.5336334109306335},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4174519181251526},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.08477035164833069},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccp48234.2019.8959661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp48234.2019.8959661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W46659105","https://openalex.org/W1480009832","https://openalex.org/W1686810756","https://openalex.org/W2002507614","https://openalex.org/W2097117768","https://openalex.org/W2104933073","https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2274287116","https://openalex.org/W2591669284","https://openalex.org/W2770241596","https://openalex.org/W2786147899","https://openalex.org/W2794825826","https://openalex.org/W2893926387","https://openalex.org/W2902853593","https://openalex.org/W2913912921","https://openalex.org/W2964350391","https://openalex.org/W3102785203","https://openalex.org/W4300485340","https://openalex.org/W6628693444","https://openalex.org/W6637373629","https://openalex.org/W6674914833","https://openalex.org/W6675634716","https://openalex.org/W6677651945","https://openalex.org/W6687483927","https://openalex.org/W6694260854","https://openalex.org/W6746693533","https://openalex.org/W6755089709","https://openalex.org/W6756785339","https://openalex.org/W6758838764","https://openalex.org/W6898611122"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W4380086463","https://openalex.org/W4225161397","https://openalex.org/W3014300295","https://openalex.org/W3164822677","https://openalex.org/W4250304930"],"abstract_inverted_index":{"Providing":[0],"reliable":[1],"computer":[2],"aid":[3],"to":[4,120],"experts":[5],"in":[6,32,105,118],"medical":[7,33],"fields":[8],"is":[9,62],"a":[10,51,88],"very":[11],"important":[12],"objective":[13],"as":[14,22,24],"it":[15],"can":[16,115],"improve":[17],"the":[18,26,38,43,57,85,94,97,102,122,128],"quality":[19],"of":[20,37,64,79,87,96,127],"healthcare,":[21],"well":[23],"reduce":[25],"associated":[27],"costs.":[28],"Most":[29],"models":[30],"used":[31],"diagnosis":[34],"use":[35],"out":[36],"box":[39],"models,":[40],"pretrained":[41],"on":[42,56],"ImageNet":[44],"dataset.":[45],"In":[46],"this":[47],"paper":[48],"we":[49,109],"introduce":[50],"deep":[52],"learning":[53],"model":[54,61],"based":[55],"Inception-ResNet":[58],"network.":[59],"The":[60],"capable":[63],"classifying":[65],"skin":[66],"lesions":[67],"from":[68],"dermoscopic":[69],"images":[70],"with":[71],"good":[72],"accuracy":[73,126],"(83.96%),":[74],"surpassing":[75],"previously":[76],"obtained":[77,104],"results":[78,103],"81.33%":[80],"and":[81,108,125],"78%.":[82],"We":[83,99],"analyze":[84],"effectiveness":[86],"few":[89],"augmentation":[90],"methods":[91],"for":[92],"increasing":[93],"performance":[95],"model.":[98,129],"also":[100],"discuss":[101],"our":[106],"experiments":[107],"present":[110],"several":[111],"potential":[112],"ways":[113],"that":[114],"be":[116],"explored":[117],"order":[119],"increase":[121],"precision,":[123],"recall":[124]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
