{"id":"W3215218792","doi":"10.1016/j.cpet.2021.06.011","title":"Artificial Intelligence and Cardiac PET/Computed Tomography Imaging","year":2021,"lang":"en","type":"review","venue":"PET Clinics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"National Institutes of Health","keywords":"Artificial intelligence; Medicine; Segmentation; Correction for attenuation; Computed tomography; Computed tomographic; Medical physics; Positron emission tomography; Computer science; Radiology","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":[0.00103285,0.00088135,0.001709174,0.003192293,0.0002457457,0.001793427,0.0007982665,0.001829693,0.005940115],"category_scores_gemma":[0.002509741,0.00035782,0.0006456921,0.00402618,0.0009498219,0.002068314,0.0007739393,0.002497023,0.00220455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008022739,"about_ca_system_score_gemma":0.001584758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00166518,"about_ca_topic_score_gemma":0.003210411,"domain_scores_codex":[0.9996854,0.00008443093,0.00005510534,0.00005679209,0.0000942917,0.00002405912],"domain_scores_gemma":[0.9981997,0.001290315,0.0001870725,0.00003289723,0.0002252191,0.00006478556],"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":[0.00006768997,0.00007756313,0.0002776424,0.0207144,0.0001225369,0.0001304626,0.00004653448,0.0004369159,0.0003594516,0.005212484,0.02754676,0.9450076],"study_design_scores_gemma":[0.00005574918,0.0001985749,0.002138908,0.01691586,0.0003927141,0.001505654,0.0001039425,0.0004805246,0.0003287379,0.006913947,0.9709156,0.00004974174],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004254303,0.9988605,0.00007854131,0.0002608215,0.0001196809,0.000002078822,0.000007830844,0.000002708356,0.0006253511],"genre_scores_gemma":[0.0004522685,0.998531,0.0001187258,0.000311795,0.0002978462,0.000003806482,0.00001436791,9.475517e-7,0.0002692844],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005940115,"threshold_uncertainty_score":0.01987165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0514167464586739,"score_gpt":0.3986133472113466,"score_spread":0.3471966007526727,"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."}}