{"id":"https://openalex.org/W3126410062","doi":"https://doi.org/10.1109/bibm49941.2020.9313266","title":"On the Deep Learning-based Age Prediction of Color Fundus Images and Correlation with Ophthalmic Diseases","display_name":"On the Deep Learning-based Age Prediction of Color Fundus Images and Correlation with Ophthalmic Diseases","publication_year":2020,"publication_date":"2020-12-16","ids":{"openalex":"https://openalex.org/W3126410062","doi":"https://doi.org/10.1109/bibm49941.2020.9313266","mag":"3126410062"},"language":"en","primary_location":{"id":"doi:10.1109/bibm49941.2020.9313266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm49941.2020.9313266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 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/A5049798592","display_name":"Yang Wen","orcid":"https://orcid.org/0000-0003-0561-6229"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yang Wen","raw_affiliation_strings":["Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017395798","display_name":"Leiting Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leiting Chen","raw_affiliation_strings":["Institute of Electronic and Information Engineering in Guangdong","Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Institute of Electronic and Information Engineering in Guangdong","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101810772","display_name":"Lifeng Qiao","orcid":"https://orcid.org/0000-0003-1023-5009"},"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"]},{"id":"https://openalex.org/I4210164131","display_name":"Ophthalmology Associates (United States)","ror":"https://ror.org/05jbhfv03","country_code":"US","type":"other","lineage":["https://openalex.org/I4210164131"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Lifeng Qiao","raw_affiliation_strings":["Ophthalmology","School of Medicine, University of Electronic Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"Ophthalmology","institution_ids":["https://openalex.org/I4210164131"]},{"raw_affiliation_string":"School of Medicine, University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101921697","display_name":"Yu Deng","orcid":"https://orcid.org/0000-0002-7637-0134"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yu Deng","raw_affiliation_strings":["King\u2019s College London, London, UK","King's College London, London, UK"],"affiliations":[{"raw_affiliation_string":"King\u2019s College London, London, UK","institution_ids":["https://openalex.org/I183935753"]},{"raw_affiliation_string":"King's College London, London, UK","institution_ids":["https://openalex.org/I183935753"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003262869","display_name":"Chuan Zhou","orcid":"https://orcid.org/0000-0001-7700-7188"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chuan Zhou","raw_affiliation_strings":["Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Media Technology of Sichuan Province, School of Computer Science and Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5049798592"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3337,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.65120059,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1171","last_page":"1175"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9818000197410583,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9607999920845032,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/fundus","display_name":"Fundus (uterus)","score":0.878394365310669},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7675819993019104},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7513560652732849},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7016475796699524},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5254021286964417},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.44063568115234375},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.42403578758239746},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.41490858793258667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38840076327323914},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.3619783818721771},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3528197705745697},{"id":"https://openalex.org/keywords/optometry","display_name":"Optometry","score":0.3283918499946594},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1327221393585205}],"concepts":[{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.878394365310669},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7675819993019104},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7513560652732849},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7016475796699524},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5254021286964417},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.44063568115234375},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.42403578758239746},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.41490858793258667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38840076327323914},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.3619783818721771},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3528197705745697},{"id":"https://openalex.org/C119767625","wikidata":"https://www.wikidata.org/wiki/Q618211","display_name":"Optometry","level":1,"score":0.3283918499946594},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1327221393585205},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm49941.2020.9313266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm49941.2020.9313266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5699999928474426,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2121939926","https://openalex.org/W2260135569","https://openalex.org/W2964121744"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2967742050"],"abstract_inverted_index":{"Color":[0],"fundus":[1,33,90,122,135,150],"imaging":[2],"is":[3],"an":[4,86],"important":[5],"modality":[6],"used":[7,73],"for":[8,18,29,79,136],"ophthalmic":[9,41,140],"disease":[10],"screening":[11],"and":[12,38,57,82,151],"provides":[13],"a":[14,74,158],"non-invasive":[15],"invivo":[16],"method":[17],"assessing":[19],"body":[20],"condition.":[21],"We":[22],"aimed":[23],"to":[24,47,129,145],"assess":[25],"deep":[26,63,107,117,125],"learning":[27,64],"models":[28,65,110,120,127],"age":[30,67,80,113,137,161],"prediction":[31,81,114,162],"from":[32],"images":[34,91],"of":[35,89,92,98,121,133,148],"normal":[36,56],"patients":[37,39],"with":[40],"diseases.":[42],"In":[43,69],"addition,":[44],"we":[45,72],"sought":[46],"investigate":[48],"interpretable":[49],"clues":[50],"regarding":[51],"the":[52,93,99,134,146,149],"salient":[53],"regions":[54],"between":[55],"pathological":[58],"changes":[59],"as":[60,104],"determined":[61],"by":[62],"during":[66],"prediction.":[68],"this":[70],"study,":[71],"convolutional":[75],"neural":[76],"network":[77],"model":[78],"evaluated":[83],"it":[84],"on":[85],"in-house":[87],"database":[88],"Chinese":[94],"population.":[95],"The":[96],"results":[97],"experiment":[100],"revealed":[101],"some":[102],"conclusions":[103],"follows:":[105],"(1)":[106],"learning-based":[108,118,126],"classification":[109],"have":[111],"better":[112],"performance":[115],"than":[116],"regression":[119],"images;":[123],"(2)":[124],"tend":[128],"use":[130],"holistic":[131],"information":[132],"prediction;":[138],"(3)":[139],"diseases":[141],"that":[142],"cause":[143],"damage":[144],"structure":[147],"change":[152],"its":[153],"appearance":[154],"will":[155],"result":[156],"in":[157,160],"decline":[159],"performance.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
