{"id":"https://openalex.org/W1982168774","doi":"https://doi.org/10.1109/jbhi.2013.2294635","title":"DREAM: Diabetic Retinopathy Analysis Using Machine Learning","display_name":"DREAM: Diabetic Retinopathy Analysis Using Machine Learning","publication_year":2014,"publication_date":"2014-01-31","ids":{"openalex":"https://openalex.org/W1982168774","doi":"https://doi.org/10.1109/jbhi.2013.2294635","mag":"1982168774","pmid":"https://pubmed.ncbi.nlm.nih.gov/25192577"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2013.2294635","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2013.2294635","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5077896212","display_name":"Sukla Roychowdhury","orcid":null},"institutions":[{"id":"https://openalex.org/I1329528197","display_name":"Minneapolis Institute of Arts","ror":"https://ror.org/019xw1562","country_code":"US","type":"archive","lineage":["https://openalex.org/I1329528197"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sohini Roychowdhury","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I1329528197"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089355316","display_name":"Dara D. Koozekanani","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dara D. Koozekanani","raw_affiliation_strings":["Department of Ophthalmology and Visual Neuroscience, University of Minnesota, Minneapolis, MN, USA","[Department of Ophthalmology and Visual Neuroscience, University of Minnesota, Minneapolis, MN, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Ophthalmology and Visual Neuroscience, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"[Department of Ophthalmology and Visual Neuroscience, University of Minnesota, Minneapolis, MN, USA]","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007884053","display_name":"Keshab K. Parhi","orcid":"https://orcid.org/0000-0001-6543-2793"},"institutions":[{"id":"https://openalex.org/I1329528197","display_name":"Minneapolis Institute of Arts","ror":"https://ror.org/019xw1562","country_code":"US","type":"archive","lineage":["https://openalex.org/I1329528197"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keshab K. Parhi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I1329528197"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.2432,"has_fulltext":false,"cited_by_count":414,"citation_normalized_percentile":{"value":0.99151149,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"18","issue":"5","first_page":"1717","last_page":"1728"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9965999722480774,"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/T10170","display_name":"Retinal Diseases and Treatments","score":0.9887999892234802,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.861929178237915},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7393893599510193},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6964756846427917},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.6367941498756409},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6347469687461853},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.5225633978843689},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4649782180786133},{"id":"https://openalex.org/keywords/diabetic-retinopathy","display_name":"Diabetic retinopathy","score":0.4502807855606079},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.43939611315727234},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3385162353515625},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1489865481853485}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.861929178237915},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7393893599510193},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6964756846427917},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6367941498756409},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6347469687461853},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.5225633978843689},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4649782180786133},{"id":"https://openalex.org/C2779829184","wikidata":"https://www.wikidata.org/wiki/Q631361","display_name":"Diabetic retinopathy","level":3,"score":0.4502807855606079},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.43939611315727234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3385162353515625},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1489865481853485},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003930","descriptor_name":"Diabetic Retinopathy","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D003930","descriptor_name":"Diabetic Retinopathy","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D003930","descriptor_name":"Diabetic Retinopathy","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D003930","descriptor_name":"Diabetic Retinopathy","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D003930","descriptor_name":"Diabetic Retinopathy","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D003930","descriptor_name":"Diabetic Retinopathy","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D003941","descriptor_name":"Diagnostic Techniques, Ophthalmological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003941","descriptor_name":"Diagnostic Techniques, Ophthalmological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003941","descriptor_name":"Diagnostic Techniques, Ophthalmological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2013.2294635","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2013.2294635","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:25192577","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25192577","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE journal of biomedical and health informatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W135725840","https://openalex.org/W1091878006","https://openalex.org/W1603281316","https://openalex.org/W1840366835","https://openalex.org/W1841361427","https://openalex.org/W1982761740","https://openalex.org/W1985390817","https://openalex.org/W1992728454","https://openalex.org/W1996151979","https://openalex.org/W2003505728","https://openalex.org/W2005394924","https://openalex.org/W2028583147","https://openalex.org/W2084318809","https://openalex.org/W2088338269","https://openalex.org/W2103614420","https://openalex.org/W2114535528","https://openalex.org/W2115185191","https://openalex.org/W2115278098","https://openalex.org/W2115531174","https://openalex.org/W2119480209","https://openalex.org/W2121737033","https://openalex.org/W2123042618","https://openalex.org/W2136289855","https://openalex.org/W2145491883","https://openalex.org/W2148989106","https://openalex.org/W2149430368","https://openalex.org/W2162698990","https://openalex.org/W2168112110","https://openalex.org/W2537306910","https://openalex.org/W2543506921","https://openalex.org/W4301347335","https://openalex.org/W6605520369","https://openalex.org/W6638831155","https://openalex.org/W6728500369"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561","https://openalex.org/W1502951582"],"abstract_inverted_index":{"This":[0,152],"paper":[1,79],"presents":[2],"a":[3,21],"computer-aided":[4],"screening":[5],"system":[6,194,208],"(DREAM)":[7],"that":[8],"analyzes":[9],"fundus":[10],"images":[11,199,231],"with":[12,157,233],"varying":[13],"illumination":[14],"and":[15,19,46,57,69,138,142,150,160,182,214,226],"fields":[16],"of":[17,77,86,104],"view,":[18],"generates":[20],"severity":[22,192,248],"grade":[23],"for":[24,50,67,89,229,246],"diabetic":[25],"retinopathy":[26,52],"(DR)":[27],"using":[28,95,168],"machine":[29,44],"learning.":[30],"Classifiers":[31],"such":[32],"as":[33,135,148,232],"the":[34,64,81,84,115,123,127,130,143,169,180,187,201,219,242],"Gaussian":[35],"Mixture":[36],"model":[37],"(GMM),":[38],"k-nearest":[39],"neighbor":[40],"(kNN),":[41],"support":[42],"vector":[43],"(SVM),":[45],"AdaBoost":[47],"are":[48,60,101,120,133,146,172],"analyzed":[49],"classifying":[51,230],"lesions":[53,132,145],"from":[54,166,200,251],"nonlesions.":[55],"GMM":[56,181],"kNN":[58,183],"classifiers":[59,66,164,184],"found":[61,173],"to":[62,174,186,218,253],"be":[63],"best":[65,220],"bright":[68,131],"red":[70,144],"lesion":[71,90,153],"classification,":[72],"respectively.":[73],"A":[74,106],"main":[75],"contribution":[76],"this":[78],"is":[80,112,195],"reduction":[82,239],"in":[83,122],"number":[85],"features":[87,100],"used":[88],"classification":[91,110,154,177],"by":[92],"feature":[93,238],"ranking":[94],"Adaboost":[96],"where":[97,114],"30":[98],"top":[99],"selected":[102],"out":[103],"78.":[105],"novel":[107],"two-step":[108],"hierarchical":[109],"approach":[111],"proposed":[113],"nonlesions":[116],"or":[117,162,234],"false":[118],"positives":[119],"rejected":[121],"first":[124],"step.":[125],"In":[126],"second":[128],"step,":[129],"classified":[134,147],"hard":[136],"exudates":[137],"cotton":[139],"wool":[140],"spots,":[141],"hemorrhages":[149],"micro-aneurysms.":[151],"problem":[155],"deals":[156],"unbalanced":[158],"datasets":[159],"SVM":[161,167],"combination":[163],"derived":[165],"Dempster-Shafer":[170],"theory":[171],"incur":[175],"more":[176],"error":[178],"than":[179],"due":[185],"data":[188],"imbalance.":[189],"The":[190,206,237],"DR":[191,247],"grading":[193],"tested":[196],"on":[197],"1200":[198],"publicly":[202],"available":[203],"MESSIDOR":[204],"dataset.":[205],"DREAM":[207],"achieves":[209],"100%":[210],"sensitivity,":[211,223],"53.16%":[212],"specificity,":[213,225],"0.904":[215],"AUC,":[216,228],"compared":[217],"reported":[221],"96%":[222],"51%":[224],"0.875":[227],"without":[235],"DR.":[236],"further":[240],"reduces":[241],"average":[243],"computation":[244],"time":[245],"per":[249],"image":[250],"59.54":[252],"3.46":[254],"s.":[255]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":49},{"year":2022,"cited_by_count":51},{"year":2021,"cited_by_count":60},{"year":2020,"cited_by_count":48},{"year":2019,"cited_by_count":46},{"year":2018,"cited_by_count":44},{"year":2017,"cited_by_count":24},{"year":2016,"cited_by_count":18},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":1}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}