{"id":"https://openalex.org/W4311597083","doi":"https://doi.org/10.1080/01969722.2022.2151176","title":"Ensemble Architecture for Prediction of Grading of Diabetic Retinopathy","display_name":"Ensemble Architecture for Prediction of Grading of Diabetic Retinopathy","publication_year":2022,"publication_date":"2022-12-05","ids":{"openalex":"https://openalex.org/W4311597083","doi":"https://doi.org/10.1080/01969722.2022.2151176"},"language":"en","primary_location":{"id":"doi:10.1080/01969722.2022.2151176","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2022.2151176","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and Systems","raw_type":"journal-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/A5052352119","display_name":"Shruti Jain","orcid":"https://orcid.org/0000-0002-7538-0584"},"institutions":[{"id":"https://openalex.org/I153954893","display_name":"Jaypee University of Information Technology","ror":"https://ror.org/00hshrf16","country_code":"IN","type":"education","lineage":["https://openalex.org/I153954893"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Shruti Jain","raw_affiliation_strings":["Department of ECE, Jaypee University of Information Technology, Solan, Himachal Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of ECE, Jaypee University of Information Technology, Solan, Himachal Pradesh, India","institution_ids":["https://openalex.org/I153954893"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046058245","display_name":"Sanket Saxena","orcid":null},"institutions":[{"id":"https://openalex.org/I153954893","display_name":"Jaypee University of Information Technology","ror":"https://ror.org/00hshrf16","country_code":"IN","type":"education","lineage":["https://openalex.org/I153954893"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sanket Saxena","raw_affiliation_strings":["Department of ECE, Jaypee University of Information Technology, Solan, Himachal Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of ECE, Jaypee University of Information Technology, Solan, Himachal Pradesh, India","institution_ids":["https://openalex.org/I153954893"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101612008","display_name":"Shivam Sinha","orcid":"https://orcid.org/0009-0000-1561-9226"},"institutions":[{"id":"https://openalex.org/I153954893","display_name":"Jaypee University of Information Technology","ror":"https://ror.org/00hshrf16","country_code":"IN","type":"education","lineage":["https://openalex.org/I153954893"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shivam Sinha","raw_affiliation_strings":["Department of ECE, Jaypee University of Information Technology, Solan, Himachal Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of ECE, Jaypee University of Information Technology, Solan, Himachal Pradesh, India","institution_ids":["https://openalex.org/I153954893"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052352119"],"corresponding_institution_ids":["https://openalex.org/I153954893"],"apc_list":null,"apc_paid":null,"fwci":0.5763,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.66395032,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"55","issue":"8","first_page":"2235","last_page":"2253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":1.0,"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":1.0,"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/T10170","display_name":"Retinal Diseases and Treatments","score":0.9882000088691711,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9868000149726868,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7824167609214783},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.771199643611908},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6733055710792542},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.6672704815864563},{"id":"https://openalex.org/keywords/diabetic-retinopathy","display_name":"Diabetic retinopathy","score":0.616746723651886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5936771631240845},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.481319785118103},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47289004921913147},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4708649218082428},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.466594934463501},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.42294448614120483},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3317970633506775},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.23037907481193542},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.08534017205238342}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7824167609214783},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.771199643611908},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6733055710792542},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.6672704815864563},{"id":"https://openalex.org/C2779829184","wikidata":"https://www.wikidata.org/wiki/Q631361","display_name":"Diabetic retinopathy","level":3,"score":0.616746723651886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5936771631240845},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.481319785118103},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47289004921913147},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4708649218082428},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.466594934463501},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.42294448614120483},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3317970633506775},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.23037907481193542},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.08534017205238342},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/01969722.2022.2151176","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2022.2151176","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W619096376","https://openalex.org/W1540549883","https://openalex.org/W1998669374","https://openalex.org/W2126975510","https://openalex.org/W2163605009","https://openalex.org/W2178629819","https://openalex.org/W2240295316","https://openalex.org/W2478483022","https://openalex.org/W2604272474","https://openalex.org/W2615982936","https://openalex.org/W2619391717","https://openalex.org/W2741346289","https://openalex.org/W2769713325","https://openalex.org/W2804383862","https://openalex.org/W2999225265","https://openalex.org/W3006492268","https://openalex.org/W3047399449","https://openalex.org/W3159064332","https://openalex.org/W3185460946"],"related_works":["https://openalex.org/W2794896638","https://openalex.org/W1807784185","https://openalex.org/W4390905871","https://openalex.org/W3202800081","https://openalex.org/W1909207154","https://openalex.org/W3124390867","https://openalex.org/W3101614107","https://openalex.org/W3204228978","https://openalex.org/W1514365828","https://openalex.org/W4390971112"],"abstract_inverted_index":{"Diabetic":[0],"Retinopathy":[1],"(DR)":[2],"is":[3,24],"a":[4,74,121,132],"diabetic":[5],"issue":[6,26],"that":[7,107,139],"influences":[8],"the":[9,13,16,20,30,43,56,96,101,114,129,140,178,185],"eyes.":[10],"It":[11],"harms":[12],"veins":[14],"of":[15,27,33,58,60,98,131],"light-delicate":[17],"tissue":[18],"behind":[19],"eye":[21],"(retina).":[22],"DR":[23,61],"an":[25,174],"diabetes":[28],"and":[29,86,151,157,161,163,182],"main":[31],"source":[32],"visual":[34],"deficiency.":[35],"Since":[36],"there":[37],"are":[38,144],"trained":[39],"doctors":[40],"to":[41,46,80],"diagnose":[42],"disease,":[44],"but":[45],"make":[47],"their":[48],"work":[49],"easier,":[50],"ensemble":[51],"architectures":[52,89],"were":[53,90],"proposed":[54,91,141,169,186],"for":[55,95,108],"prediction":[57],"grading":[59],"using":[62,92],"modern":[63],"technology":[64],"known":[65,124],"as":[66,125],"deep":[67],"learning.":[68],"Deep":[69],"neural":[70],"network":[71],"results":[72,172],"in":[73,78,173],"better":[75],"diagnostic":[76],"system":[77],"comparison":[79],"machine":[81],"learning":[82,133],"networks.":[83],"ResNET":[84,152],"101":[85,153,188],"Ensemble":[87,150,170],"CNN":[88],"Adam":[93],"Optimization":[94],"detection":[97],"DR.":[99],"From":[100],"results,":[102],"it":[103,135],"has":[104],"been":[105],"observed":[106],"any":[109],"constant":[110],"size":[111],"Network":[112],"architecture,":[113],"loss":[115],"cannot":[116],"be":[117],"further":[118],"reduced":[119],"after":[120,146],"certain":[122],"number":[123],"Bayes":[126],"error.":[127],"With":[128],"help":[130],"curve,":[134],"can":[136],"easily":[137],"understand":[138],"architecture":[142],"costs":[143],"decreasing":[145],"every":[147],"iteration.":[148],"The":[149,168],"model":[154,171,181],"attain":[155],"87.67%":[156],"81.28%":[158],"accuracy,":[159],"respectively,":[160],"0.5046":[162],"0.5328":[164],"cross-entropy":[165],"loss,":[166],"respectively.":[167],"18.4%":[175],"improvement":[176],"over":[177,184],"Inception":[179],"V3":[180],"7.8%":[183],"ResNet":[187],"model.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
