{"id":"W2975022009","doi":"","title":"Training of deep convolutional neural nets to extract radiomic signatures of tumors","year":2019,"lang":"en","type":"article","venue":"","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Convolutional neural network; Artificial intelligence; Voxel; Pattern recognition (psychology); Computer science; Histogram; Radiomics; Feature (linguistics); Minimum bounding box; Deep learning; Image (mathematics); Process (computing)","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":[0.0006047321,0.001179171,0.0004934056,0.0005442436,0.0001886657,0.0004396556,0.0009730286,0.0008864453,0.001280395],"category_scores_gemma":[0.001706805,0.0005543851,0.0005804476,0.0003865477,0.000389406,0.0005347387,0.0005164312,0.0008813143,0.0003930119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001260791,"about_ca_system_score_gemma":0.0009869044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025746,"about_ca_topic_score_gemma":0.01121334,"domain_scores_codex":[0.9998183,0.00002153611,0.0000084491,0.00006174633,0.00004943727,0.00004052811],"domain_scores_gemma":[0.999568,0.0001897132,0.00007196364,0.00003769767,0.0001089234,0.00002364596],"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":[0.0001627412,0.0001486594,0.004939087,0.00008627932,0.00009464767,0.00007498624,0.00002692436,0.8822674,0.01858775,0.0006850457,0.001106904,0.09181955],"study_design_scores_gemma":[0.000003107756,0.00002261177,0.0005361135,0.000003719824,0.000006626296,0.000008120318,0.000002044773,0.9961552,0.002972533,0.0001851612,0.0001021088,0.000002730622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4942829,0.0008615267,0.496,0.0003240785,0.0001209173,0.0001613537,0.0009710572,0.003613947,0.003664211],"genre_scores_gemma":[0.8977979,0.0001745225,0.09833764,0.0001224121,0.00001991793,0.0001151334,0.001329805,0.0000793388,0.002023316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01025746,"threshold_uncertainty_score":0.02039552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01373380099068883,"score_gpt":0.2902369975954875,"score_spread":0.2765031966047987,"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."}}