{"id":"W4283773504","doi":"10.3390/diagnostics12071607","title":"Diabetic Retinopathy Detection from Fundus Images of the Eye Using Hybrid Deep Learning Features","year":2022,"lang":"en","type":"article","venue":"Diagnostics","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Prince Mohammad Bin Fahd University; Commonwealth Cyber Initiative","keywords":"Diabetic retinopathy; Artificial intelligence; Fundus (uterus); Computer science; Convolutional neural network; Pattern recognition (psychology); Retina; Feature (linguistics); Retinopathy; Feature extraction; Support vector machine; Computer vision; Ophthalmology; Medicine; Diabetes mellitus","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001729085,0.0001017293,0.0002140502,0.00007378728,0.0002957179,0.00001901275,0.0001057303,0.00002079731,0.00009067654],"category_scores_gemma":[0.001614574,0.00008036889,0.0001398395,0.0002777823,0.00007639547,0.00002323267,0.0001285456,0.0004829344,0.000002957716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006606236,"about_ca_system_score_gemma":0.00002604706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000338828,"about_ca_topic_score_gemma":0.000003711996,"domain_scores_codex":[0.9989724,0.0001788649,0.0001828375,0.0001795351,0.000327301,0.0001590508],"domain_scores_gemma":[0.9990813,0.0003994998,0.0001528005,0.0002425291,0.00007756183,0.00004626868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006274951,0.0001778626,0.8514526,0.00005798831,0.0001557286,0.0001325508,0.0005323143,0.009357382,0.1133322,0.000006005409,0.0004131169,0.02431943],"study_design_scores_gemma":[0.0009164228,0.0003421771,0.6536951,0.0002420551,0.001921063,0.00008935701,0.001643698,0.0341847,0.3035325,0.0003750697,0.002747847,0.0003099643],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961793,0.002127482,0.0006779718,0.0003205168,0.0002770562,0.00009778282,0.00002696513,0.00003486609,0.000258074],"genre_scores_gemma":[0.9988711,0.000135899,0.0003225327,0.0001689389,0.0001398237,0.000008379413,0.00002840882,0.00002135513,0.0003035407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1977576,"threshold_uncertainty_score":0.3277348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008561041427438455,"score_gpt":0.247544086546006,"score_spread":0.2389830451185675,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}