{"id":"W4213194625","doi":"10.3390/electronics11040605","title":"Deep Learning Models for Predicting Epileptic Seizures Using iEEG Signals","year":2022,"lang":"en","type":"article","venue":"Electronics","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Epilepsy; Convolutional neural network; Electroencephalography; Artificial intelligence; Transfer of learning; Computer science; Deep learning; Epileptic seizure; Machine learning; Pattern recognition (psychology); Neuroscience; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.0004097765,0.0001501278,0.0001702118,0.00009027693,0.0009356788,0.00009150905,0.0003763836,0.00003512969,0.00005965467],"category_scores_gemma":[0.0001716135,0.0001593348,0.00009784925,0.0002368304,0.00003039782,0.0001991009,0.0001912221,0.0005301601,0.000002589862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001886247,"about_ca_system_score_gemma":0.0001062882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003769085,"about_ca_topic_score_gemma":0.000004283953,"domain_scores_codex":[0.9981858,0.0002146989,0.0002319959,0.0004359497,0.0002991027,0.0006325045],"domain_scores_gemma":[0.9991058,0.0005239222,0.0001384811,0.0001514122,0.00002766934,0.00005277874],"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":[0.00003016855,0.00003388158,0.00003064961,0.0000141133,0.000008321207,0.000005723067,0.0007291663,0.8024995,0.1908408,0.001436192,0.00009909813,0.004272371],"study_design_scores_gemma":[0.0002421281,0.0004731991,0.000001224789,0.000008242202,0.00001452489,0.00008192003,0.0001427313,0.896726,0.08908779,0.005087212,0.007971149,0.0001638691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8306568,0.002043131,0.165749,0.0001443081,0.0003046971,0.0003763554,0.000007468895,0.0002249196,0.0004932695],"genre_scores_gemma":[0.9974861,0.00003873594,0.001245583,0.0005325744,0.0001370315,0.00005767586,0.00000372576,0.00004038717,0.0004582389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1668292,"threshold_uncertainty_score":0.719658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04386123311823762,"score_gpt":0.2821266210245931,"score_spread":0.2382653879063555,"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."}}