{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005743057,0.0006402843,0.0004212148,0.00102522,0.0002348233,0.0005670929,0.0008537202,0.0006692219,0.0007796773],"category_scores_gemma":[0.0012968,0.0002127486,0.0005542588,0.000612919,0.0002115023,0.0006011251,0.000546099,0.0009459714,0.0003135707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009934836,"about_ca_system_score_gemma":0.0005655395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0123951,"about_ca_topic_score_gemma":0.009557169,"domain_scores_codex":[0.9997328,0.00005419143,0.00001477422,0.00006924668,0.0000680595,0.00006093539],"domain_scores_gemma":[0.9996783,0.0001010325,0.00004833399,0.00004153138,0.0001033241,0.00002744711],"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":[0.0007068793,0.0009375521,0.01738986,0.000107963,0.0002190585,0.0003294751,0.00007874817,0.3499275,0.01632542,0.001633141,0.006884342,0.60546],"study_design_scores_gemma":[0.000008772927,0.00005710523,0.001635084,0.00000754177,0.00001236381,0.00003585263,0.00001436144,0.9940144,0.003155442,0.000763936,0.0002881108,0.000007059242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7029783,0.002929565,0.2814503,0.001118778,0.0002443947,0.0001730069,0.0009899301,0.004273316,0.005842431],"genre_scores_gemma":[0.9572384,0.0003763042,0.03879265,0.0001951057,0.00005885114,0.00004347895,0.000916114,0.00002520581,0.002353944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0123951,"threshold_uncertainty_score":0.02464592,"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."}}