{"id":"W4390145386","doi":"10.18280/isi.280624","title":"Enhanced Detection of Diabetic Retinopathy Using Ensemble Machine Learning: A Comparative Study","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diabetic retinopathy; Artificial intelligence; Ensemble learning; Computer science; Retinopathy; Machine learning; Medicine; Optometry; Diabetes mellitus; Endocrinology","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":[0.002264444,0.0007209833,0.001179597,0.002240359,0.0002877309,0.0008943843,0.0005486497,0.0007278121,0.0004427514],"category_scores_gemma":[0.003476015,0.0001217273,0.0008452286,0.001070954,0.000162341,0.000648601,0.0004981314,0.0004915367,0.0002255516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003413953,"about_ca_system_score_gemma":0.0003262121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003655387,"about_ca_topic_score_gemma":0.002689395,"domain_scores_codex":[0.9991139,0.0002682612,0.00006729811,0.0001860654,0.0002570334,0.0001074431],"domain_scores_gemma":[0.9979531,0.0008167276,0.000122303,0.0002028096,0.0007842653,0.000120841],"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":[0.002871664,0.001151962,0.1098943,0.000488268,0.001273425,0.0005929222,0.0002182779,0.1244338,0.01350861,0.0007654806,0.00717862,0.7376226],"study_design_scores_gemma":[0.0000401337,0.001235504,0.05424281,0.000057156,0.0005369622,0.000529508,0.0002014247,0.9303004,0.009835924,0.0006419812,0.002312242,0.00006599302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9053169,0.008711779,0.07937358,0.0003693997,0.0003759584,0.000113312,0.0008395644,0.001122881,0.003776531],"genre_scores_gemma":[0.9779716,0.001202287,0.01904367,0.00007528561,0.0001124503,0.00002113681,0.0009919782,0.00002669378,0.0005547726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003655387,"threshold_uncertainty_score":0.01197565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03074828514223635,"score_gpt":0.2943467709007509,"score_spread":0.2635984857585145,"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."}}