{"id":"W3111633653","doi":"10.1016/j.ejmp.2020.11.027","title":"Validation of low-dose lung cancer PET-CT protocol and PET image improvement using machine learning","year":2020,"lang":"en","type":"article","venue":"Physica Medica","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network","funders":"National University Cancer Institute, Singapore","keywords":"Voxel; Image quality; Random forest; Nuclear medicine; Lesion; Protocol (science); Artificial intelligence; Computer science; Medicine; Mathematics; Image (mathematics); Pathology","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":[0.003914145,0.0004835959,0.0004378394,0.000651357,0.0003259149,0.0007849875,0.0007556669,0.0007814249,0.001388109],"category_scores_gemma":[0.006781702,0.0002821645,0.0003809422,0.0004202694,0.0005138921,0.0004583048,0.0003648599,0.0004385854,0.0005161739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000606764,"about_ca_system_score_gemma":0.0009492664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002258508,"about_ca_topic_score_gemma":0.002090476,"domain_scores_codex":[0.99891,0.0003604874,0.000110138,0.0002364524,0.0003283377,0.00005461622],"domain_scores_gemma":[0.9971741,0.001171145,0.0002455408,0.0004051961,0.0009525328,0.00005132953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005445061,0.001515024,0.06740543,0.00110069,0.0005764793,0.0002811872,0.0003318966,0.09331878,0.5423948,0.0009481817,0.002309788,0.2843727],"study_design_scores_gemma":[0.0003201326,0.003112789,0.1090899,0.00007715524,0.0009819475,0.001027383,0.0001524486,0.3473992,0.5316491,0.0005602061,0.005533193,0.0000966023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8024126,0.001255199,0.1877781,0.0002554589,0.0001591078,0.001013711,0.001224368,0.0021613,0.003740105],"genre_scores_gemma":[0.9081348,0.0003079842,0.0878601,0.0001563437,0.00002423634,0.0003955934,0.001433928,0.0002669011,0.001420141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003914145,"threshold_uncertainty_score":0.02070022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02279809784730139,"score_gpt":0.3636088330551311,"score_spread":0.3408107352078298,"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."}}