{"id":"W4410145946","doi":"10.1007/s11517-025-03366-2","title":"Using baseline MRI radiomic features to predict the efficacy of repetitive transcranial magnetic stimulation in Alzheimer’s patients","year":2025,"lang":"en","type":"article","venue":"Medical & Biological Engineering & Computing","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Brain Institute; McGill University; Riverview Hospital; University of Winnipeg; University of Manitoba; Research Manitoba","funders":"Weston Brain Institute","keywords":"Transcranial magnetic stimulation; Human physiology; Baseline (sea); Magnetic resonance imaging; Neuroscience; Medicine; Stimulation; Physical medicine and rehabilitation; Biomedical engineering; Psychology; Internal medicine; Radiology; Biology","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":[0.0005051611,0.0003731985,0.0004493296,0.0005351726,0.0001921617,0.0005461703,0.000162248,0.0005846154,0.0008149108],"category_scores_gemma":[0.00229428,0.0001228524,0.0003868216,0.0002178408,0.0002080169,0.0004189684,0.0001368807,0.0004316293,0.0002262844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001855899,"about_ca_system_score_gemma":0.0001700925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001164002,"about_ca_topic_score_gemma":0.001737708,"domain_scores_codex":[0.9998567,0.00003328949,0.00003092748,0.0000308076,0.00002594134,0.00002237685],"domain_scores_gemma":[0.9990692,0.0004532954,0.0002029677,0.00005546176,0.00009961976,0.000119657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001949836,0.0002208477,0.984401,0.00002280685,0.0002042506,0.0002712182,0.00005812741,0.0002708132,0.002765474,0.00002480836,0.0001802916,0.009630555],"study_design_scores_gemma":[0.0000318751,0.0009041586,0.9965681,0.000008186859,0.0001233413,0.0005019397,0.00008391287,0.001064635,0.0005059293,0.00006213885,0.0001363893,0.00000941216],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986086,0.0003504762,0.0001251141,0.00004886278,0.00001662934,0.000006639886,0.0001150075,0.00000788764,0.0007207106],"genre_scores_gemma":[0.9994869,0.0000993818,0.0000838179,0.00002228695,0.0000226656,0.000004545153,0.0001825855,0.000001384299,0.00009644842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001164002,"threshold_uncertainty_score":0.002726138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02168317269237177,"score_gpt":0.322012220983465,"score_spread":0.3003290482910933,"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."}}