{"id":"W4380872237","doi":"10.1097/icu.0000000000000979","title":"Current status and practical considerations of artificial intelligence use in screening and diagnosing retinal diseases: Vision Academy retinal expert consensus","year":2023,"lang":"en","type":"review","venue":"Current Opinion in Ophthalmology","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; St. Michael's Hospital; International Federation on Ageing","funders":"National Medical Research Council; Chugai Pharmaceutical; Allergan; Duke-NUS Medical School; Santen; Agency for Science, Technology and Research; Apellis Pharmaceuticals; Bayer HealthCare; Alimera Sciences; Medical Research Council; Biogen; Mylan; Bayer Yakuhin; Novo Nordisk; Bausch Health; Alexion Pharmaceuticals","keywords":"Medicine; Artificial intelligence; Telemedicine; Applications of artificial intelligence; Data science; Computer science; Health care","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005965274,0.0006226556,0.002081359,0.003608231,0.0004194078,0.002330594,0.00211061,0.0029511,0.004172885],"category_scores_gemma":[0.0126954,0.0003874299,0.001544392,0.003323424,0.0009506929,0.002521439,0.001313958,0.003213,0.001858859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001474541,"about_ca_system_score_gemma":0.006793499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002663537,"about_ca_topic_score_gemma":0.003721527,"domain_scores_codex":[0.998355,0.0004103819,0.0004335957,0.0001834341,0.0005255456,0.00009204909],"domain_scores_gemma":[0.98761,0.007984975,0.0009210378,0.0001900149,0.002988064,0.0003059337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008396776,0.00003806148,0.0002169167,0.05816662,0.0002340689,0.0001388709,0.0001258041,0.0002407058,0.0002640847,0.004996286,0.06180559,0.873689],"study_design_scores_gemma":[0.00003237949,0.00009232093,0.001011251,0.07383364,0.000606931,0.0007490636,0.0002170207,0.000134618,0.0002693002,0.004299452,0.9187117,0.00004223766],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004390563,0.9956023,0.0001232838,0.002917243,0.0005650063,0.000007912815,0.00002450606,0.000005416059,0.0007104954],"genre_scores_gemma":[0.0005687852,0.9969888,0.0002918685,0.001442159,0.0004558061,0.00001525656,0.00003675952,0.000002713655,0.0001978436],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005965274,"threshold_uncertainty_score":0.03154778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.39203021898638,"score_gpt":0.542920687648063,"score_spread":0.150890468661683,"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."}}