{"id":"W2806322961","doi":"10.1016/j.nicl.2018.08.019","title":"Structural neuroimaging as clinical predictor: A review of machine learning applications","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":184,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fondation Brain Canada","keywords":"Neuroimaging; Functional magnetic resonance imaging; Magnetic resonance imaging; Brain disease; Disease; Medical imaging","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003762219,0.001227344,0.001924473,0.004324035,0.0003278983,0.001708456,0.001500954,0.001475023,0.00203599],"category_scores_gemma":[0.009170367,0.0006299768,0.001115974,0.005065104,0.0009651133,0.001888392,0.0008281738,0.001877884,0.001194685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009138784,"about_ca_system_score_gemma":0.001310811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002132712,"about_ca_topic_score_gemma":0.001863853,"domain_scores_codex":[0.9988956,0.0003424489,0.0001840136,0.0002527908,0.0002816682,0.00004353069],"domain_scores_gemma":[0.9913458,0.00719659,0.0002888136,0.0001876226,0.0008831795,0.00009810592],"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":[0.0001097101,0.00009382983,0.002754817,0.006818728,0.0002017189,0.0001250186,0.00007125988,0.002411392,0.0004789179,0.005741575,0.01043063,0.9707625],"study_design_scores_gemma":[0.00009038838,0.001039369,0.02134616,0.0290465,0.001655754,0.004663081,0.0004403911,0.03061428,0.005775469,0.05516154,0.849788,0.0003790885],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008690931,0.9883456,0.007864008,0.001072507,0.0002223033,0.00002118856,0.00007982262,0.00004980483,0.001475628],"genre_scores_gemma":[0.01714659,0.9664506,0.01344686,0.0007257585,0.001344741,0.00006829567,0.000208405,0.00003585637,0.0005728059],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004324035,"threshold_uncertainty_score":0.01989675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1205252195923044,"score_gpt":0.4213833487128944,"score_spread":0.30085812912059,"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."}}