{"id":"https://openalex.org/W7101629680","doi":"https://doi.org/10.48550/arxiv.2510.23325","title":"Multitask Multimodal Self-Supervised Learning for Medical Images","display_name":"Multitask Multimodal Self-Supervised Learning for Medical Images","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7101629680","doi":"https://doi.org/10.48550/arxiv.2510.23325"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2510.23325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.23325","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2510.23325","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Simionescu, Cristian","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Simionescu, Cristian","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"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":true,"primary_topic":{"id":"https://openalex.org/T11776","display_name":"Irish and British Studies","score":0.621999979019165,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11776","display_name":"Irish and British Studies","score":0.621999979019165,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14292","display_name":"Migration, Policy, and Dickens Studies","score":0.027400000020861626,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12872","display_name":"Philippine History and Culture","score":0.019300000742077827,"subfield":{"id":"https://openalex.org/subfields/3314","display_name":"Anthropology"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5976999998092651},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5426999926567078},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5110999941825867},{"id":"https://openalex.org/keywords/pretext","display_name":"Pretext","score":0.4505999982357025},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.4390000104904175},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.40720000863075256},{"id":"https://openalex.org/keywords/medical-diagnosis","display_name":"Medical diagnosis","score":0.3903000056743622},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.38029998540878296},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.352400004863739}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7598000168800354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.650600016117096},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5976999998092651},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5426999926567078},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5110999941825867},{"id":"https://openalex.org/C2779627259","wikidata":"https://www.wikidata.org/wiki/Q779763","display_name":"Pretext","level":3,"score":0.4505999982357025},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.4390000104904175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4228000044822693},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.40720000863075256},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.3903000056743622},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.38029998540878296},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.352400004863739},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.31349998712539673},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.31349998712539673},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.29840001463890076},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2808000147342682},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.2687999904155731},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.2513999938964844},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2510.23325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.23325","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2510.23325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.23325","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,95,120,183],"thesis":[1,75,151,213],"works":[2],"to":[3,23,52,60,73,137,206,215],"address":[4],"a":[5,57,115,127,224,247],"pivotal":[6],"challenge":[7],"in":[8,69,159,201,244,251,257],"medical":[9,70,103,131,160,219,258],"image":[10,104,132,220],"analysis:":[11],"the":[12,24,39,62,77,80,143,150,153,179,191,194,198,216,236,252],"reliance":[13,230],"on":[14,38,101,145,231],"extensive":[15],"labeled":[16,147,232],"datasets,":[17,105],"which":[18],"are":[19,168],"often":[20],"limited":[21],"due":[22],"need":[25],"for":[26,88,238],"expert":[27],"annotation":[28],"and":[29,33,45,64,91,109,111,124],"constrained":[30],"by":[31,222],"privacy":[32],"legal":[34],"issues.":[35],"By":[36],"focusing":[37],"development":[40,78],"of":[41,66,79,126,130,156,170,193,218,254],"self-supervised":[42,157],"learning":[43,68,90,158,202,256],"techniques":[44],"domain":[46,93],"adaptation":[47,118],"methods,":[48],"this":[49,74,212],"research":[50],"aims":[51],"circumvent":[53],"these":[54],"limitations,":[55],"presenting":[56],"novel":[58,164],"approach":[59,184],"enhance":[61],"utility":[63],"efficacy":[65],"deep":[67,92,255],"imaging.":[71,161,259],"Central":[72],"is":[76,97,112,185],"Medformer,":[81],"an":[82],"innovative":[83],"neural":[84],"network":[85],"architecture":[86],"designed":[87],"multitask":[89],"adaptation.":[94],"model":[96],"adept":[98],"at":[99],"pre-training":[100],"diverse":[102],"handling":[106],"varying":[107],"sizes":[108],"modalities,":[110],"equipped":[113],"with":[114],"dynamic":[116],"input-output":[117],"mechanism.":[119],"enables":[121],"efficient":[122,241],"processing":[123],"integration":[125],"wide":[128],"range":[129],"types,":[133],"from":[134,174],"2D":[135],"X-rays":[136],"complex":[138],"3D":[139],"MRIs,":[140],"thus":[141],"mitigating":[142],"dependency":[144],"large":[146],"datasets.":[148],"Further,":[149],"explores":[152],"current":[154],"state":[155],"It":[162,234],"introduces":[163],"pretext":[165],"tasks":[166],"that":[167,228],"capable":[169],"extracting":[171],"meaningful":[172],"information":[173],"unlabeled":[175],"data,":[176],"significantly":[177],"advancing":[178],"model's":[180,199],"interpretative":[181],"abilities.":[182],"validated":[186],"through":[187],"rigorous":[188],"experimentation,":[189],"including":[190],"use":[192],"MedMNIST":[195],"dataset,":[196],"demonstrating":[197],"proficiency":[200],"generalized":[203],"features":[204],"applicable":[205],"various":[207],"downstream":[208],"tasks.":[209],"In":[210],"summary,":[211],"contributes":[214],"advancement":[217],"analysis":[221],"offering":[223],"scalable,":[225],"adaptable":[226],"framework":[227],"reduces":[229],"data.":[233],"paves":[235],"way":[237],"more":[239],"accurate,":[240],"diagnostic":[242],"tools":[243],"healthcare,":[245],"signifying":[246],"major":[248],"step":[249],"forward":[250],"application":[253]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-29T00:00:00"}
