{"id":"W3158720037","doi":"10.1002/mp.14909","title":"A deep learning‐based model for characterization of atherosclerotic plaque in coronary arteries using optical coherence tomography  images","year":2021,"lang":"en","type":"article","venue":"Medical Physics","topic":"Coronary Interventions and Diagnostics","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; École de Technologie Supérieure","funders":"","keywords":"Optical coherence tomography; Artificial intelligence; Coronary arteries; Computer science; Segmentation; Coronary atherosclerosis; Vulnerable plaque; Computer vision; Medical imaging; Medicine; Biomedical engineering; Radiology; Artery; Coronary artery disease; Pathology; Internal medicine","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":[0.0005095945,0.0007105017,0.0006458643,0.0006323429,0.0002360577,0.0006441591,0.001007231,0.001127721,0.0009502541],"category_scores_gemma":[0.0009152793,0.0003602311,0.0007436256,0.0004182603,0.0003621425,0.0005916221,0.0005492402,0.001069632,0.0003109249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007726552,"about_ca_system_score_gemma":0.0008568272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01257426,"about_ca_topic_score_gemma":0.00910126,"domain_scores_codex":[0.9998102,0.00003385578,0.00001100741,0.00006290586,0.00004088509,0.00004124358],"domain_scores_gemma":[0.9998083,0.00007054743,0.00002997563,0.00001224427,0.0000655749,0.0000133863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001875891,0.0001547625,0.002708032,0.00007136155,0.00008791008,0.0001317976,0.00004481503,0.8612201,0.008078408,0.002184445,0.002079185,0.1230516],"study_design_scores_gemma":[0.000001865703,0.000009692178,0.0001062729,0.000002413602,0.000004287891,0.000006750504,0.000001069623,0.9992612,0.0002905029,0.0002400445,0.0000742648,0.000001662015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08291107,0.001147277,0.9117243,0.0007072245,0.00009198121,0.00007582051,0.0003282681,0.001035354,0.001978811],"genre_scores_gemma":[0.9022288,0.0007787402,0.09037068,0.0004229316,0.00008677682,0.0002147112,0.0006851521,0.00006152553,0.005150703],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01257426,"threshold_uncertainty_score":0.02500212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03188894200590674,"score_gpt":0.2928286729677486,"score_spread":0.2609397309618418,"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."}}