{"id":"https://openalex.org/W4313527133","doi":"https://doi.org/10.1109/bibm55620.2022.9994890","title":"Pre-MocoDiagnosis: Few-Shot Ophthalmic Diseases Recognition using Contrastive Learning","display_name":"Pre-MocoDiagnosis: Few-Shot Ophthalmic Diseases Recognition using Contrastive Learning","publication_year":2022,"publication_date":"2022-12-06","ids":{"openalex":"https://openalex.org/W4313527133","doi":"https://doi.org/10.1109/bibm55620.2022.9994890"},"language":"en","primary_location":{"id":"doi:10.1109/bibm55620.2022.9994890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm55620.2022.9994890","pdf_url":null,"source":{"id":"https://openalex.org/S4363607730","display_name":"2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"article","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/A5021986551","display_name":"Anping Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Anping Cai","raw_affiliation_strings":["University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017395798","display_name":"Leiting Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leiting Chen","raw_affiliation_strings":["University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731","Institute of Electronic and Information Engineering of UESTC in Guangdong, Dongguan, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Institute of Electronic and Information Engineering of UESTC in Guangdong, Dongguan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101551232","display_name":"Yongqi Chen","orcid":"https://orcid.org/0000-0002-8243-9468"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongqi Chen","raw_affiliation_strings":["University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073391006","display_name":"Jiahao Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahao Fang","raw_affiliation_strings":["University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013821522","display_name":"Mengqi Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengqi Sun","raw_affiliation_strings":["University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003262869","display_name":"Chuan Zhou","orcid":"https://orcid.org/0000-0001-7700-7188"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhou Chuan","raw_affiliation_strings":["University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering,Chengdu,Sichuan Province,China,611731","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5021986551"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":4.5,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.9516129,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2059","last_page":"2066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12599","display_name":"Retinal and Optic Conditions","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"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/T12599","display_name":"Retinal and Optic Conditions","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"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/T11194","display_name":"Ocular Diseases and Beh\u00e7et\u2019s Syndrome","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"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/T11438","display_name":"Retinal Imaging and Analysis","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/overfitting","display_name":"Overfitting","score":0.8946878910064697},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7644335627555847},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7164472341537476},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6192560791969299},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5877799987792969},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5724118947982788},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.495625376701355},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4929978549480438},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40829959511756897},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.31953781843185425},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28047990798950195},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08702188730239868}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8946878910064697},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7644335627555847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7164472341537476},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6192560791969299},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5877799987792969},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5724118947982788},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.495625376701355},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4929978549480438},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40829959511756897},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31953781843185425},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28047990798950195},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08702188730239868},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm55620.2022.9994890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm55620.2022.9994890","pdf_url":null,"source":{"id":"https://openalex.org/S4363607730","display_name":"2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W2031489346","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2296283641","https://openalex.org/W2550068010","https://openalex.org/W2601450892","https://openalex.org/W2798836702","https://openalex.org/W2903240400","https://openalex.org/W2932083555","https://openalex.org/W2954913281","https://openalex.org/W2963070905","https://openalex.org/W2963732628","https://openalex.org/W2963741406","https://openalex.org/W2989893062","https://openalex.org/W3012209922","https://openalex.org/W3034748927","https://openalex.org/W3114726686","https://openalex.org/W3134072853","https://openalex.org/W3176469180","https://openalex.org/W3205249428","https://openalex.org/W3209654711","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6753081716","https://openalex.org/W6756965382","https://openalex.org/W6758126075","https://openalex.org/W6761152059","https://openalex.org/W6770467399","https://openalex.org/W6775093496","https://openalex.org/W6779525423","https://openalex.org/W6803279866"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W3099765033","https://openalex.org/W3128011703","https://openalex.org/W2795259429"],"abstract_inverted_index":{"The":[0,123],"use":[1],"of":[2,29,37,43,60,71,76,100,104,110,125,155,170,179,204],"deep":[3,50,83,314],"learning":[4,174,264,271,297,308,330],"networks":[5,45,51,84],"for":[6,17,48,52,79,161,176,290],"medical":[7,18,53],"image":[8,211],"classification":[9,300],"is":[10,216,224,251,265],"becoming":[11],"increasingly":[12],"popular.":[13],"However,":[14],"annotated":[15],"datasets":[16],"diagnosis":[19,54],"are":[20,46,63,237,320],"still":[21,272],"difficult":[22],"to":[23,26,67,141,145,164,210,219,221],"obtain":[24],"due":[25],"the":[27,35,39,44,68,74,98,102,108,139,146,150,156,159,162,167,171,177,205,213,248,274,278,282,291,305,312,327],"Limitations":[28],"expertise":[30],"and":[31,41,55,73,85,93,112,135,152,158,223,241,285,298,322],"expensive":[32],"consumption.":[33],"In":[34],"absence":[36,109],"datasets,":[38,288],"effectiveness,":[40],"robustness":[42],"weak":[47],"traditional":[49,82,299,313],"problems":[56],"with":[57,229,277],"these":[58],"kinds":[59],"data":[61,72,78,111],"issues":[62],"quite":[64],"common.":[65],"Due":[66,144],"long-tailed":[69,113],"distribution":[70],"lack":[75],"labeling":[77],"some":[80],"diseases,":[81],"training":[86,239,249,318],"techniques":[87],"can":[88,185],"suffer":[89],"from":[90],"significant":[91],"overfitting":[92],"poor":[94],"generalization.":[95],"We":[96],"examine":[97],"issue":[99],"locating":[101],"locations":[103],"impacted":[105],"lesions":[106],"in":[107,120,331],"distributions":[114],"by":[115],"building":[116],"on":[117,166,267,334],"recent":[118],"developments":[119],"contrastive":[121,173],"learning.":[122],"processing":[124],"each":[126],"image\u2014that":[127],"is,":[128],"its":[129],"division":[130],"into":[131],"multiple":[132],"smaller":[133],"pictures":[134],"comparison":[136],"between":[137,149],"them\u2014improves":[138],"ability":[140],"identify":[142,187],"illnesses.":[143],"modest":[147],"variations":[148],"sick":[151],"healthy":[153],"areas":[154],"disease":[157],"necessity":[160],"network":[163,214,276,301,315],"concentrate":[165],"diseased":[168],"portions":[169],"disease,":[172],"allows":[175],"maintenance":[178],"intra-class":[180],"undistorted":[181],"properties.":[182],"Our":[183],"technique":[184],"swiftly":[186],"an":[188],"image\u2019s":[189],"essential":[190],"details":[191],"while":[192],"masking":[193],"as":[194],"much":[195],"superfluous":[196],"information":[197],"a":[198,202,242],"spossible.":[199],"A":[200],"s":[201],"result":[203],"pre-trained":[206],"network\u2019s":[207],"increased":[208],"sensitivity":[209],"attributes,":[212],"model":[215],"better":[217,310],"able":[218],"generalize":[220],"samples":[222,240,319],"more":[225],"resilient":[226],"when":[227,235,247,317],"dealing":[228],"small":[230],"sample":[231],"sizes.":[232],"Classification":[233],"models":[234],"there":[236],"few":[238],"long":[243],"tail":[244],"distribution;":[245],"however,":[246],"dataset":[250],"bigger,":[252],"our":[253,289,323],"method":[254],"does":[255],"not":[256],"necessarily":[257],"worse":[258],"than":[259,311],"conventional":[260,268],"approaches,":[261],"because":[262],"few-shot":[263,270,296,307,329],"based":[266],"techniques,":[269],"trains":[273],"classical":[275,306,328],"basis":[279],"tasks.":[280],"On":[281],"ISIC":[283],"2018":[284],"internal":[286],"ophthalmology":[287],"first":[292],"time":[293],"tests":[294],"comparing":[295],"approachesd":[302],"emonstrate":[303],"that":[304],"performs":[309],"approach":[316,325],"few,":[321],"suggested":[324],"outperforms":[326],"task":[332],"setting":[333],"both":[335],"datasets.":[336]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}