{"id":"https://openalex.org/W4416765901","doi":"https://doi.org/10.48550/arxiv.2511.19535","title":"Masked Autoencoder Joint Learning for Robust Spitzoid Tumor Classification","display_name":"Masked Autoencoder Joint Learning for Robust Spitzoid Tumor Classification","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W4416765901","doi":"https://doi.org/10.48550/arxiv.2511.19535"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2511.19535","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.19535","pdf_url":"https://arxiv.org/pdf/2511.19535","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2511.19535","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020570581","display_name":"Il\u00e1n Carretero","orcid":"https://orcid.org/0009-0003-9474-6515","observed_orcids":["https://orcid.org/0009-0003-9474-6515"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carretero, Il\u00e1n","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070291119","display_name":"R. Mahtani","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mahtani, Roshni","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051549684","display_name":"Silvia P\u00e9rez\u2010Deb\u00e9n","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Perez-Deben, Silvia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102727435","display_name":"Jos\u00e9 Gonz\u00e1lez","orcid":"https://orcid.org/0000-0002-9832-3355","observed_orcids":["https://orcid.org/0000-0002-9832-3355"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gonz\u00e1lez-Mu\u00f1oz, Jos\u00e9 Francisco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030244533","display_name":"Carlos Couceiro Monteagudo","orcid":"https://orcid.org/0000-0002-9381-9976","observed_orcids":["https://orcid.org/0000-0002-9381-9976"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Monteagudo, Carlos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043316752","display_name":"Valery Naranjo","orcid":"https://orcid.org/0000-0002-0181-3412","observed_orcids":["https://orcid.org/0000-0002-0181-3412"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naranjo, Valery","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067714499","display_name":"Roc\u00edo del Amor","orcid":"https://orcid.org/0000-0002-5342-2093","observed_orcids":["https://orcid.org/0000-0002-5342-2093"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"del Amor, Roc\u00edo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"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/T10885","display_name":"Gene expression and cancer classification","score":0.7710000276565552,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.7710000276565552,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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"}},{"id":"https://openalex.org/T10269","display_name":"Epigenetics and DNA Methylation","score":0.06989999860525131,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.031599998474121094,"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":[{"id":"https://openalex.org/keywords/dna-methylation","display_name":"DNA methylation","score":0.875},{"id":"https://openalex.org/keywords/epigenetic-information","display_name":"epigenetic information","score":0.7120000123977661},{"id":"https://openalex.org/keywords/missing-data","display_name":"missing data","score":0.796999990940094},{"id":"https://openalex.org/keywords/masked-autoencoder","display_name":"masked autoencoder","score":0.8460000157356262},{"id":"https://openalex.org/keywords/tumor-classification","display_name":"tumor classification","score":0.7289999723434448},{"id":"https://openalex.org/keywords/high-dimensional-data","display_name":"high-dimensional data","score":0.6570000052452087},{"id":"https://openalex.org/keywords/skin-cancer-diagnosis","display_name":"skin cancer diagnosis","score":0.4090000092983246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6690000295639038},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6317999958992004},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5964000225067139},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4970000088214874},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4765999913215637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4410000145435333},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.429500013589859},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41999998688697815},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3400000035762787},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C2983685735","wikidata":"https://www.wikidata.org/wiki/Q5227355","display_name":"Data source","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C2988416141","wikidata":"https://www.wikidata.org/wiki/Q6031139","display_name":"Information loss","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2540999948978424},{"id":"https://openalex.org/C142210648","wikidata":"https://www.wikidata.org/wiki/Q1266546","display_name":"Record linkage","level":3,"score":0.2533999979496002},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2511.19535","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.19535","pdf_url":"https://arxiv.org/pdf/2511.19535","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2511.19535","doi":"https://doi.org/10.48550/arxiv.2511.19535","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.19535","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2511.19535","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.19535","pdf_url":"https://arxiv.org/pdf/2511.19535","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.504800021648407,"display_name":"Good health and well-being"}],"sustainable_development_goals_aurora":[],"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":{"Accurate":[0],"diagnosis":[1],"of":[2,29,68,104],"spitzoid":[3],"tumors":[4],"(ST)":[5],"is":[6,107],"critical":[7],"to":[8,14,51,71,97],"ensure":[9],"a":[10,26],"favorable":[11,61],"prognosis":[12],"and":[13,18,54,63,80,93],"avoid":[15],"both":[16],"under-":[17],"over-treatment.":[19],"Epigenetic":[20],"data,":[21,39],"particularly":[22],"DNA":[23],"methylation,":[24],"provide":[25],"valuable":[27],"source":[28],"information":[30],"for":[31],"this":[32],"task.":[33],"However,":[34],"prior":[35],"studies":[36],"assume":[37],"complete":[38,79],"an":[40,66],"unrealistic":[41],"setting":[42],"as":[43],"methylation":[44],"profiles":[45],"frequently":[46],"contain":[47],"missing":[48],"entries":[49],"due":[50],"limited":[52],"coverage":[53],"experimental":[55],"artifacts.":[56],"Our":[57],"work":[58],"challenges":[59],"these":[60],"scenarios":[62],"introduces":[64],"ReMAC,":[65],"extension":[67],"ReMasker":[69],"designed":[70],"tackle":[72],"classification":[73,99],"tasks":[74],"on":[75,84],"high-dimensional":[76],"data":[77,87],"under":[78],"incomplete":[81],"regimes.":[82],"Evaluation":[83],"real":[85],"clinical":[86],"demonstrates":[88],"that":[89],"ReMAC":[90],"achieves":[91],"strong":[92],"robust":[94],"performance":[95],"compared":[96],"competing":[98],"methods":[100],"in":[101],"the":[102],"stratification":[103],"ST.":[105],"Code":[106],"available:":[108],"https://github.com/roshni-mahtani/ReMAC.":[109]},"counts_by_year":[],"updated_date":"2026-09-22T06:50:58.402377","created_date":"2025-11-28T00:00:00"}