{"id":"https://openalex.org/W7225267692","doi":"https://doi.org/10.5281/zenodo.23952373","title":"Ante-hoc Framework for Interpretable Skin Lesion Classification","display_name":"Ante-hoc Framework for Interpretable Skin Lesion Classification","publication_year":2026,"publication_date":"2026-11-04","ids":{"openalex":"https://openalex.org/W7225267692","doi":"https://doi.org/10.5281/zenodo.23952373"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.23952373","doi":"https://doi.org/10.5281/zenodo.23952373","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23952373","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"volume":null,"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.23952373","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5160574466","display_name":"Daphne Panopoulou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I200777214","display_name":"National and Kapodistrian University of Athens","ror":"https://ror.org/04gnjpq42","country_code":"GR","type":"education","lineage":["https://openalex.org/I200777214"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Panopoulou, Daphne","raw_affiliation_strings":["National and Kapodistrian University of Athens","Suite5 Data Intelligence Services, Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National and Kapodistrian University of Athens","institution_ids":["https://openalex.org/I200777214"]},{"raw_affiliation_string":"Suite5 Data Intelligence Services, Athens, Greece","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076332895","display_name":"Dionysis Xenakis","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210103741","display_name":"Global Digital Technologies (Greece)","ror":"https://ror.org/01c4p0b96","country_code":"GR","type":"company","lineage":["https://openalex.org/I4210103741"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Xenakis, Dionysis","raw_affiliation_strings":["Department of Digital Industry Technologies at the National and Kapodistrian, University of Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Digital Industry Technologies at the National and Kapodistrian, University of Athens, Greece","institution_ids":["https://openalex.org/I4210103741"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046638814","display_name":"Dimitris Panopoulos","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Panopoulos, Dimitris","raw_affiliation_strings":["Suite5 Data Intelligence Services, Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Suite5 Data Intelligence Services, Athens, Greece","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128250700","display_name":"Sotiris Koussouris","orcid":"https://orcid.org/0000-0002-0675-9400","observed_orcids":["https://orcid.org/0000-0002-0675-9400"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koussouris, Sotiris","raw_affiliation_strings":["Suite5 Data Intelligence Services, Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Suite5 Data Intelligence Services, Athens, Greece","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.83694583,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.6035000085830688,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.6035000085830688,"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":0.37700000405311584,"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":0.003100000089034438,"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"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8858000040054321},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7167999744415283},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7085000276565552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6761000156402588},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6665999889373779},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.559499979019165},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5264000296592712},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5253000259399414},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.4507000148296356},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4058000147342682},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.36329999566078186},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.353300005197525},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33160001039505005},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C2988168687","wikidata":"https://www.wikidata.org/wiki/Q949302","display_name":"Skin lesion","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27469998598098755},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C98025372","wikidata":"https://www.wikidata.org/wiki/Q477538","display_name":"Systems architecture","level":3,"score":0.25270000100135803}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.23952373","doi":"https://doi.org/10.5281/zenodo.23952373","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23952373","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},{"id":"doi:10.5281/zenodo.23952374","doi":"https://doi.org/10.5281/zenodo.23952374","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23952374","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.5281/zenodo.23952373","doi":"https://doi.org/10.5281/zenodo.23952373","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23952373","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"high":[1],"reported":[2],"accuracy":[3,95,100],"in":[4,40,123,135],"automated":[5],"dermatological":[6],"screening,":[7],"many":[8],"deep":[9],"learning":[10],"ensembles":[11],"remain":[12],"limited":[13,121],"by":[14],"opaque":[15],"architectures":[16],"and":[17,103,131,143],"reliance":[18],"on":[19],"post-hoc":[20],"explainability":[21],"methods.":[22],"This":[23],"paper":[24],"proposes":[25],"a":[26,47,54,58,98],"lightweight":[27],"ante-hoc":[28,63],"semantic":[29],"framework":[30,91],"optimized":[31],"for":[32],"low-latency":[33],"edge":[34],"execution":[35],"to":[36,50,57,72,140],"minimize":[37],"bandwidth":[38],"overhead":[39],"decentralized":[41],"clinical":[42,142],"networks.":[43],"The":[44,126],"architecture":[45,68],"uses":[46],"knowledge-distillation":[48],"pipeline":[49],"transfer":[51],"representations":[52],"from":[53],"foundation":[55],"model":[56,66],"computationallyefficient":[59],"student":[60],"model.":[61],"An":[62],"concept":[64],"bottleneck":[65],"(CBM)":[67],"constrains":[69],"the":[70,80,90,107],"network":[71],"predict":[73],"eight":[74],"dermoscopy-derived":[75],"visual":[76],"concepts":[77],"before":[78],"producing":[79],"final":[81],"lesion":[82],"label.":[83],"On":[84],"HAM10000,":[85],"an":[86,93,104],"anonymized":[87],"public":[88],"dataset,":[89],"achieves":[92],"overall":[94],"of":[96,101,110],"90.75%,":[97],"balanced":[99],"84.55%,":[102],"area":[105],"under":[106],"curve":[108],"(AUC)":[109],"more":[111],"than":[112],"0.9500,":[113],"suggesting":[114],"that":[115],"interpretability":[116],"can":[117],"be":[118],"introduced":[119],"with":[120],"loss":[122],"discriminative":[124],"performance.":[125],"resultingconcept-based":[127],"predictions":[128],"are":[129],"auditable":[130],"could":[132],"support":[133],"clinicians":[134],"prioritizing":[136],"high-risk":[137],"cases,":[138],"subject":[139],"further":[141],"deployment":[144],"studies.":[145]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-05T00:00:00"}