{"id":"W2208039604","doi":"10.1186/s12911-015-0227-6","title":"Data mining EEG signals in depression for their diagnostic value","year":2015,"lang":"en","type":"article","venue":"BMC Medical Informatics and Decision Making","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ottawa Mental Health Centre; McGill University; University of Ottawa","funders":"Mitacs; University of Ottawa","keywords":"Linear discriminant analysis; Electroencephalography; Artificial intelligence; Pattern recognition (psychology); Normalization (sociology); Computer science; Major depressive disorder; Decision tree; Wavelet; Data mining; Psychology; Psychiatry; Cognition","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":[0.001418559,0.000546607,0.0006126069,0.002147163,0.0002023865,0.0007379952,0.0006372586,0.0004420217,0.0006475492],"category_scores_gemma":[0.004805019,0.0001100576,0.0005709216,0.001288174,0.0002096619,0.0003636053,0.000270474,0.000493284,0.0003240241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003347298,"about_ca_system_score_gemma":0.0004338122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001076287,"about_ca_topic_score_gemma":0.001024226,"domain_scores_codex":[0.9994547,0.0001549882,0.00009549858,0.0001189674,0.0001369509,0.00003890861],"domain_scores_gemma":[0.9973879,0.001367244,0.0003857487,0.0001675572,0.0006200778,0.00007149891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001615705,0.001027741,0.4546111,0.0008446985,0.0006217792,0.0007420505,0.0003317196,0.01882353,0.03909274,0.0006046089,0.0033344,0.4783499],"study_design_scores_gemma":[0.0002445623,0.00224241,0.4433701,0.000466934,0.001080021,0.002420078,0.001124156,0.4867391,0.05122469,0.005154514,0.005842206,0.00009122738],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9193971,0.002732034,0.07193524,0.000925726,0.0001087768,0.0003939152,0.002560375,0.0005110433,0.001435932],"genre_scores_gemma":[0.9618906,0.0004711048,0.03584465,0.0000461052,0.00004016515,0.0001111407,0.00144156,0.000009189681,0.0001454385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002147163,"threshold_uncertainty_score":0.007502139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1702386496777006,"score_gpt":0.3898401140350743,"score_spread":0.2196014643573737,"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."}}