{"id":"W4404360459","doi":"10.18280/ts.410541","title":"Diabetic Retinopathy Recognition and Classification Using Transfer Learning Deep Neural Networks","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transfer of learning; Computer science; Artificial intelligence; Artificial neural network; Deep learning; Diabetic retinopathy; Pattern recognition (psychology); Medicine; Diabetes mellitus","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002890596,0.0001212431,0.0001655209,0.0001280683,0.00009597594,0.0001001172,0.00002359799,0.00004670678,0.0002159712],"category_scores_gemma":[0.00001242731,0.0001054945,0.00008682948,0.0002204646,0.00005312098,0.0001053682,0.000006063531,0.0002602818,0.0000106776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003843306,"about_ca_system_score_gemma":0.00001106539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009450518,"about_ca_topic_score_gemma":8.595668e-7,"domain_scores_codex":[0.9990631,0.00008243116,0.0002288733,0.0002635824,0.0001767232,0.0001852373],"domain_scores_gemma":[0.9997333,0.00005532334,0.00001929276,0.00005673018,0.00004685663,0.00008854388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002298083,0.0001541017,0.03813972,0.0005590112,0.000308613,0.0001926664,0.001793292,0.006838941,0.2009484,0.00006016546,0.00007187876,0.7507034],"study_design_scores_gemma":[0.0003447462,0.0001594611,0.008609925,0.0002287647,0.0005639626,0.00006816788,0.0002033431,0.9890093,0.0004792022,0.00004123558,0.0001731881,0.0001186896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9186267,0.0009956157,0.07925225,0.0006033005,0.00006743081,0.0001326809,0.000001567922,0.0001113539,0.0002091086],"genre_scores_gemma":[0.9989939,0.00007901693,0.0003112427,0.0001407608,0.0002849598,0.00001025251,0.00009332727,0.000022097,0.00006440235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9821703,"threshold_uncertainty_score":0.4301941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0429199823625503,"score_gpt":0.2715405288330492,"score_spread":0.228620546470499,"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."}}