{"id":"W2790418083","doi":"10.1117/12.2295214","title":"Automatic detection of anatomical regions in frontal x-ray images: comparing convolutional neural networks to random forest","year":2018,"lang":"en","type":"article","venue":"Medical Imaging 2018: Computer-Aided Diagnosis","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Random forest; Convolutional neural network; Computer science; Artificial intelligence; Pattern recognition (psychology); Computer vision","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":[0.0006999581,0.0003292621,0.0007738009,0.0004811367,0.0001191207,0.00007497778,0.0004976979,0.0001341745,0.0002034732],"category_scores_gemma":[0.0005330137,0.0003164391,0.0002176502,0.0007310911,0.0004863545,0.0002266969,0.0001982892,0.0005612982,0.00005192309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001818376,"about_ca_system_score_gemma":0.000040214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005596697,"about_ca_topic_score_gemma":0.0002552406,"domain_scores_codex":[0.9970425,0.0001793255,0.0009192239,0.0004599199,0.0007318968,0.000667113],"domain_scores_gemma":[0.9979819,0.0008148782,0.00009746841,0.0003724404,0.000108167,0.0006251191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006265166,0.0006651346,0.4489773,0.0002624047,0.0003766567,0.0002324515,0.0006493068,0.1414856,0.0005589592,0.00007803241,0.06188146,0.34477],"study_design_scores_gemma":[0.001838085,0.00003841705,0.04287677,0.0005073812,0.00006467262,0.00002750453,0.00003154465,0.9535401,0.0002814798,0.00007592476,0.0004206775,0.0002973981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4286736,0.0003282007,0.5685682,0.0008523868,0.001042056,0.0001713441,0.000003997185,0.0002930147,0.00006717173],"genre_scores_gemma":[0.9938601,0.00004937778,0.004405786,0.0005718624,0.0009492246,0.00008887364,0.00002455075,0.00004550879,0.000004738744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8120545,"threshold_uncertainty_score":0.9999288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008842432153715853,"score_gpt":0.2336383409855434,"score_spread":0.2247959088318275,"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."}}