{"id":"W4223526023","doi":"10.1016/j.brachy.2022.02.005","title":"Approaching automated applicator digitization from a new angle: Using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy","year":2022,"lang":"en","type":"article","venue":"Brachytherapy","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Jewish General Hospital; McGill University Health Centre; Mila - Quebec Artificial Intelligence Institute; McGill University","funders":"","keywords":"Prostate brachytherapy; Brachytherapy; Medicine; Segmentation; Artificial intelligence; Nuclear medicine; Data set; Sagittal plane; Digitization; Computer vision; Computer science; Radiology; Radiation therapy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002584471,0.0004231153,0.0004735668,0.0002426614,0.0004552839,0.0002552934,0.0002777518,0.00006101005,0.0001680182],"category_scores_gemma":[0.00001323057,0.0004579404,0.00007547065,0.0006999521,0.00004994748,0.0007408221,0.0001322494,0.0005564064,0.000001092413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001961813,"about_ca_system_score_gemma":0.0001084111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001805601,"about_ca_topic_score_gemma":0.00001202749,"domain_scores_codex":[0.9976192,0.0002845729,0.0004826057,0.0008211108,0.0002467048,0.0005458613],"domain_scores_gemma":[0.9988777,0.0001776131,0.0003594946,0.0003672794,0.00004363078,0.0001742735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005271373,0.0002772164,0.04420386,0.00001507524,0.0001409815,0.0000131574,0.003107197,0.1657708,0.220001,0.0006370287,0.00006852076,0.5652379],"study_design_scores_gemma":[0.01300717,0.001194864,0.04924342,0.0001425691,0.00006436183,0.00002949359,0.002176038,0.8638697,0.04416761,0.01328587,0.00958927,0.003229694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6238154,0.0004100272,0.3739104,0.0001299709,0.00007209842,0.001080827,0.00006984151,0.0004858188,0.00002561757],"genre_scores_gemma":[0.9290738,0.00005476615,0.0691682,0.0002789612,0.0003362254,0.0005212486,0.0002644652,0.0001726938,0.0001296229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6980988,"threshold_uncertainty_score":0.9997872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008300139603694481,"score_gpt":0.2670173584631079,"score_spread":0.2587172188594135,"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."}}