{"id":"W3110662188","doi":"10.1109/ehb50910.2020.9280267","title":"Low Latency Automated Epileptic Seizure Detection: Individualized vs. Global Approaches","year":2020,"lang":"en","type":"article","venue":"2020 International Conference on e-Health and Bioengineering (EHB)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bishop's University","funders":"","keywords":"Latency (audio); Epilepsy; Computer science; Epileptic seizure; Electroencephalography; Artificial neural network; Artificial intelligence; Pattern recognition (psychology); Sensitivity (control systems); Computational complexity theory; Machine learning; Speech recognition; Algorithm; Neuroscience; Psychology; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005899601,0.0009906244,0.0006709861,0.001059543,0.0001767617,0.0009192305,0.0003385067,0.0004488349,0.001182239],"category_scores_gemma":[0.001855677,0.0001691159,0.0003171827,0.0006809942,0.0002234914,0.000899821,0.0007313528,0.0003975807,0.0007573716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001914819,"about_ca_system_score_gemma":0.0002927434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009730588,"about_ca_topic_score_gemma":0.002777847,"domain_scores_codex":[0.9995506,0.0001347006,0.00002906894,0.0001281704,0.000111367,0.00004598118],"domain_scores_gemma":[0.9994549,0.0002507922,0.00008767507,0.00009362157,0.00008655748,0.00002642464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004446159,0.0001493629,0.02490406,0.000175868,0.0001543424,0.0001480759,0.00009315283,0.05828615,0.02827317,0.001155606,0.002040441,0.8841751],"study_design_scores_gemma":[0.00005582766,0.0008661431,0.0885252,0.0000794416,0.0002441468,0.001163953,0.0003088751,0.8672443,0.02959671,0.006860865,0.004976338,0.00007814972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3094704,0.003112421,0.6764259,0.0006989859,0.00008261613,0.0001237989,0.0006786605,0.002856475,0.006550849],"genre_scores_gemma":[0.9129564,0.0008710866,0.08253603,0.00009383592,0.0000716412,0.00005347894,0.0004966287,0.0001197009,0.002801288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001182239,"threshold_uncertainty_score":0.003954947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07075192858293305,"score_gpt":0.2926919140598637,"score_spread":0.2219399854769307,"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."}}