{"id":"W2806424800","doi":"10.1016/j.jcjo.2018.04.019","title":"Deep learning in ophthalmology: a review","year":2018,"lang":"en","type":"review","venue":"Canadian Journal of Ophthalmology","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":143,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Deep learning; Optical coherence tomography; Macular degeneration; Modalities; Glaucoma; Optometry; Diabetic retinopathy; Medicine; Cataracts; Computer science; Artificial intelligence; Ophthalmology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001515393,0.0004533836,0.004257665,0.001779923,0.00008252468,0.00002343106,0.0004734725,0.0004827181,0.004357704],"category_scores_gemma":[0.001829553,0.0003579511,0.00122639,0.00104226,0.0003403629,0.00006461007,0.00002863458,0.001968783,0.0002120933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004848884,"about_ca_system_score_gemma":0.004232326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001168724,"about_ca_topic_score_gemma":0.00003660612,"domain_scores_codex":[0.9963058,0.0007814918,0.001648941,0.0003775975,0.0001986679,0.0006875034],"domain_scores_gemma":[0.996797,0.0002172217,0.001217313,0.0003912311,0.0004042403,0.0009729917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"case_report","study_design_scores_codex":[0.00001871724,0.00006040523,0.006625196,0.05076077,0.0009729363,0.728841,0.00007143028,0.00000187329,1.087375e-7,0.00001751685,0.003646273,0.2089838],"study_design_scores_gemma":[0.0001285932,0.0003452141,0.00007956814,0.05421386,0.001343557,0.5120848,0.000009959842,0.000002549168,2.577114e-8,0.00001716729,0.4316233,0.0001512989],"study_design_candidate":"case_report","study_design_consensus":"case_report","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001594905,0.9771001,0.000002891847,0.00033555,0.000420276,0.0002799403,0.000003911556,0.000003468373,0.02169435],"genre_scores_gemma":[0.000831161,0.9944205,0.0003289467,0.00008389301,0.0004765334,0.00001139264,0.00004522657,0.00007251616,0.003729854],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4279771,"threshold_uncertainty_score":0.9998872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06710786722469497,"score_gpt":0.3817603809811355,"score_spread":0.3146525137564405,"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."}}