乐胖代购免代理版

{"id":"https://openalex.org/W4310978402","doi":"https://doi.org/10.48550/arxiv.2206.13079","title":"Dynamic Bank Learning for Semi-supervised Federated Image Diagnosis with Class Imbalance","display_name":"Dynamic Bank Learning for Semi-supervised Federated Image Diagnosis with Class Imbalance","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4310978402","doi":"https://doi.org/10.48550/arxiv.2206.13079"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2206.13079","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_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2206.13079","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042130198","display_name":"Meirui Jiang","orcid":"https://orcid.org/0000-0003-4228-8420"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Meirui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012016311","display_name":"Hongzheng Yang","orcid":"https://orcid.org/0009-0003-0292-3829"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Hongzheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100458660","display_name":"Xiaoxiao Li","orcid":"https://orcid.org/0000-0003-1612-0691"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xiaoxiao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054960327","display_name":"Quande Liu","orcid":"https://orcid.org/0000-0002-3921-5960"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Quande","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032708386","display_name":"Pheng\u2010Ann Heng","orcid":"https://orcid.org/0000-0003-3055-5034"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heng, Pheng-Ann","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5090516040","display_name":"Qi Dou","orcid":"https://orcid.org/0000-0002-3416-9950"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dou, Qi","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":59},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9922,"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":0.9922,"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":0.9915,"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/T11330","display_name":"Systemic Sclerosis and Related Diseases","score":0.9272,"subfield":{"id":"https://openalex.org/subfields/2734","display_name":"Pathology and Forensic Medicine"},"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/code","display_name":"Code (set theory)","score":0.5439406}],"concepts":[{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.75335383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7257122},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.63984793},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.608617},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5763524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5544436},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5439406},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.42080647},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39222544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.333809},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09646419},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2206.13079","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_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.13079","pdf_url":"http://arxiv.org/pdf/2206.13079","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2206.13079","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2206.13079","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_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.53}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4312518048","https://openalex.org/W4236520801","https://openalex.org/W2996769815","https://openalex.org/W2484602794","https://openalex.org/W2122599759","https://openalex.org/W2105887828","https://openalex.org/W1995022398","https://openalex.org/W1975289146","https://openalex.org/W1537234410","https://openalex.org/W115923022"],"abstract_inverted_index":{"Despite":[0],"recent":[1],"progress":[2],"on":[3,122,164],"semi-supervised":[4,40],"federated":[5],"learning":[6,73],"(FL)":[7],"for":[8,24,100],"medical":[9,126],"image":[10],"diagnosis,":[11],"the":[12,53,91,105,110,129,162,165],"problem":[13,36,65],"of":[14,37,60,87,147],"imbalanced":[15,39],"class":[16,38,81,98,116],"distributions":[17],"among":[18],"unlabeled":[19,50],"clients":[20,46],"is":[21,66,174],"still":[22],"unsolved":[23],"real-world":[25,125],"use.":[26],"In":[27],"this":[28],"paper,":[29],"we":[30],"study":[31],"a":[32,57,69],"practical":[33],"yet":[34],"challenging":[35],"FL":[41],"(imFed-Semi),":[42],"which":[43,75],"allows":[44],"all":[45],"to":[47,95,108,113],"have":[48],"only":[49],"data":[51],"while":[52],"server":[54],"just":[55],"has":[56,150],"small":[58],"amount":[59],"labeled":[61],"data.":[62],"This":[63,84],"imFed-Semi":[64],"addressed":[67],"by":[68,79],"novel":[70],"dynamic":[71,92],"bank":[72,93],"scheme,":[74],"improves":[76],"client":[77],"training":[78],"exploiting":[80],"proportion":[82],"information.":[83],"scheme":[85],"consists":[86],"two":[88,123],"parts,":[89],"i.e.,":[90],"construction":[94],"distill":[96],"various":[97],"proportions":[99],"each":[101],"local":[102,111],"client,":[103],"and":[104,137,158],"sub-bank":[106],"classification":[107],"impose":[109],"model":[112],"learn":[114],"different":[115],"proportions.":[117],"We":[118],"evaluate":[119],"our":[120,148],"approach":[121],"public":[124],"datasets,":[127],"including":[128],"intracranial":[130],"hemorrhage":[131],"diagnosis":[132,140],"with":[133,141,153,161],"25,000":[134],"CT":[135],"slices":[136],"skin":[138],"lesion":[139],"10,015":[142],"dermoscopy":[143],"images.":[144],"The":[145],"effectiveness":[146],"method":[149],"been":[151],"validated":[152],"significant":[154],"performance":[155],"improvements":[156],"(7.61%":[157],"4.69%)":[159],"compared":[160],"second-best":[163],"accuracy,":[166],"as":[167,169],"well":[168],"comprehensive":[170],"analytical":[171],"studies.":[172],"Code":[173],"available":[175],"at":[176],"https://github.com/med-air/imFedSemi.":[177]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4310978402","counts_by_year":[],"updated_date":"2025-03-02T00:12:55.942840","created_date":"2022-12-22"}