{"id":"https://openalex.org/W4396852801","doi":"https://doi.org/10.1145/3647444.3647918","title":"Advancement In Melanoma Detection: A Comprehensive Review On Deep Learning Based Classification Approaches","display_name":"Advancement In Melanoma Detection: A Comprehensive Review On Deep Learning Based Classification Approaches","publication_year":2023,"publication_date":"2023-11-23","ids":{"openalex":"https://openalex.org/W4396852801","doi":"https://doi.org/10.1145/3647444.3647918"},"language":"en","primary_location":{"id":"doi:10.1145/3647444.3647918","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3647444.3647918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Information Management & Machine Intelligence","raw_type":"proceedings-article"},"type":"review","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/A5097955621","display_name":"Rani Suresh Mohadikar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146358","display_name":"Raisoni Group of Institutions","ror":"https://ror.org/03dp11s58","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210146358"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Rani Suresh Mohadikar","raw_affiliation_strings":["Computer Science, G. H. Raisoni College of Engineering Nagpur, Maharashtra, India"],"affiliations":[{"raw_affiliation_string":"Computer Science, G. H. Raisoni College of Engineering Nagpur, Maharashtra, India","institution_ids":["https://openalex.org/I4210146358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067336453","display_name":"Chetan Dhule","orcid":"https://orcid.org/0000-0003-4116-9251"},"institutions":[{"id":"https://openalex.org/I4210146358","display_name":"Raisoni Group of Institutions","ror":"https://ror.org/03dp11s58","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210146358"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chetan Ashokrao Dhule","raw_affiliation_strings":["Data Science, G H Raisoni College of Engineering Nagpur, India"],"affiliations":[{"raw_affiliation_string":"Data Science, G H Raisoni College of Engineering Nagpur, India","institution_ids":["https://openalex.org/I4210146358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5097955621"],"corresponding_institution_ids":["https://openalex.org/I4210146358"],"apc_list":null,"apc_paid":null,"fwci":0.1748,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.60891193,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.998199999332428,"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":0.998199999332428,"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/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9950000047683716,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.673688530921936},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5313186049461365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.528217077255249},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37689700722694397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.673688530921936},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5313186049461365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.528217077255249},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37689700722694397}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3647444.3647918","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3647444.3647918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Information Management & Machine Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2070773792","https://openalex.org/W2128084896","https://openalex.org/W2183341477","https://openalex.org/W2955471158","https://openalex.org/W2963163009","https://openalex.org/W2964081807","https://openalex.org/W2964350391","https://openalex.org/W3003544448","https://openalex.org/W3090140268","https://openalex.org/W3158076558","https://openalex.org/W3158307528","https://openalex.org/W3202169040","https://openalex.org/W3212558710","https://openalex.org/W4200120391","https://openalex.org/W4205895239","https://openalex.org/W4206055728","https://openalex.org/W4214575762","https://openalex.org/W4214867134","https://openalex.org/W4214874219","https://openalex.org/W4224297054","https://openalex.org/W4281679852","https://openalex.org/W4281703109","https://openalex.org/W4283526860","https://openalex.org/W4283757235","https://openalex.org/W4290612991","https://openalex.org/W4293067010","https://openalex.org/W4297537493","https://openalex.org/W4304761908","https://openalex.org/W4306786599","https://openalex.org/W4306955476","https://openalex.org/W4310131915","https://openalex.org/W4311959437","https://openalex.org/W4313503250","https://openalex.org/W4379932692","https://openalex.org/W4379932916","https://openalex.org/W4379932966"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127","https://openalex.org/W3082895349"],"abstract_inverted_index":{"The":[0,38,52,120,184,211],"most":[1],"deadly":[2],"type":[3],"of":[4,34,61,70,83,124,137,166,172,187],"skin":[5],"cancer,":[6],"melanoma,":[7],"poses":[8],"a":[9],"serious":[10],"public":[11],"health":[12],"problem,":[13],"and":[14,40,63,73,88,104,122,135,148,176,194,209,216,222,242],"early":[15],"detection":[16,75],"is":[17,199,226],"essential":[18],"for":[19,92,132,179,230],"enhancing":[20,246],"patient":[21],"outcomes.":[22],"Deep":[23],"learning-based":[24],"classification":[25,156],"techniques":[26,141],"have":[27],"recently":[28],"demonstrated":[29],"incredible":[30],"promise":[31],"in":[32,42,48,97,118,191,196],"terms":[33],"revolutionising":[35],"melanoma":[36,62,85,138,174],"detection.":[37],"developments":[39],"innovations":[41],"this":[43,49],"subject":[44],"are":[45,116,127,151],"thoroughly":[46],"explored":[47],"in-depth":[50],"review.":[51],"study":[53],"starts":[54],"out":[55],"by":[56],"going":[57],"over":[58],"the":[59,68,81,90,164,170,205],"epidemiology":[60],"its":[64],"rising":[65],"prevalence,":[66],"highlighting":[67],"significance":[69],"creating":[71],"reliable":[72],"precise":[74],"techniques.":[76],"It":[77,225],"draws":[78],"attention":[79],"to":[80,95,142],"shortcomings":[82],"conventional":[84],"diagnosis":[86],"methods":[87,229],"emphasises":[89],"potential":[91],"deep":[93,113,180],"learning":[94,114,147,181],"fill":[96],"these":[98,197,233],"gaps.":[99],"Convolutional":[100],"neural":[101,106],"networks":[102,107],"(CNNs)":[103],"recurrent":[105],"(RNNs),":[108],"Xception,":[109],"ResNet,":[110],"among":[111],"other":[112],"models,":[115],"examined":[117],"detail.":[119],"advantages":[121],"disadvantages":[123],"each":[125],"strategy":[126],"compared,":[128],"illuminating":[129],"their":[130,177],"applicability":[131,208],"various":[133],"stages":[134],"types":[136],"lesions.":[139],"As":[140],"improve":[143],"model":[144,182,220,247],"performance,":[145],"transfer":[146],"ensemble":[149],"approaches":[150],"investigated.":[152],"This":[153],"promotes":[154],"robust":[155],"even":[157],"with":[158,201,232],"small":[159],"datasets.This":[160],"paper":[161,212],"also":[162,213],"discusses":[163],"value":[165],"augmented":[167],"data,":[168],"addressing":[169],"dearth":[171],"annotated":[173],"photos":[175],"implications":[178],"training.":[183],"critical":[185],"importance":[186],"explainable":[188],"artificial":[189],"intelligence":[190],"fostering":[192],"transparency":[193],"trust":[195],"models":[198],"highlighted,":[200],"an":[202],"emphasis":[203],"on":[204],"results'":[206],"clinical":[207],"interpretability.":[210],"acknowledges":[214],"difficulties":[215],"constraints":[217],"like":[218],"interpretability,":[219],"generalisation,":[221],"ethical":[223],"considerations.":[224],"suggested":[227],"that":[228],"dealing":[231],"problems":[234],"be":[235],"used,":[236],"including":[237],"as":[238],"incorporating":[239],"dermatological":[240],"knowledge":[241],"continuing":[243],"research":[244],"into":[245],"explainability.":[248]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}