{"id":"W4402674501","doi":"10.1136/jnis-2024-022254","title":"Automated detection of large vessel occlusion using deep learning: a pivotal multicenter study and reader performance study","year":2024,"lang":"en","type":"article","venue":"Journal of NeuroInterventional Surgery","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Korea Medical Device Development Fund","keywords":"Medicine; Receiver operating characteristic; Confidence interval; Stroke (engine); Occlusion; Multicenter study; Radiology; Internal medicine; Randomized controlled trial","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01055984,0.0009106003,0.0008750404,0.001098076,0.0002835585,0.001111948,0.000844962,0.001146278,0.0008663867],"category_scores_gemma":[0.01509562,0.0004075821,0.0007461392,0.0007758622,0.000575696,0.0009398817,0.0007139487,0.0004700132,0.0005068789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004741476,"about_ca_system_score_gemma":0.0003239871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009761792,"about_ca_topic_score_gemma":0.001077042,"domain_scores_codex":[0.9948316,0.002660706,0.0003433545,0.001292808,0.0007050204,0.0001665448],"domain_scores_gemma":[0.9823078,0.006674499,0.004452064,0.002144908,0.0035841,0.0008367359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01897256,0.00144185,0.9262008,0.0002421113,0.001857689,0.0001774403,0.0005208319,0.001895004,0.004690705,0.00009309401,0.001089874,0.04281802],"study_design_scores_gemma":[0.001580873,0.008823164,0.965351,0.00007732527,0.001239841,0.00101332,0.0002193838,0.01657343,0.00315835,0.0001896898,0.001697388,0.00007621857],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964166,0.0008695408,0.001516071,0.00007161494,0.0000216704,0.00008732171,0.0004859882,0.00004796604,0.0004832911],"genre_scores_gemma":[0.9973144,0.0001754887,0.001249349,0.00006410811,0.0000469336,0.00006336595,0.0008929067,0.00001730403,0.0001760768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01055984,"threshold_uncertainty_score":0.05584645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03015742784886051,"score_gpt":0.315452052560845,"score_spread":0.2852946247119845,"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."}}