{"id":"W4377089525","doi":"10.1109/ner52421.2023.10123759","title":"Screening of Mild Cognitive Impairment in Patients with Parkinson's Disease Using a Variational Mode Decomposition Based Deep-Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Movement Disorders","funders":"National Institutes of Health","keywords":"Dementia; Cognition; Electroencephalography; Parkinson's disease; Audiology; Sleep architecture; Cognitive impairment; Disease; Medicine; Artificial intelligence; Physical medicine and rehabilitation; Psychology; Computer science; Psychiatry; Internal medicine; Polysomnography","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":[0.0004647764,0.0004074857,0.0003846993,0.0003571679,0.0001230882,0.000304631,0.0003638271,0.0004487483,0.0004354867],"category_scores_gemma":[0.00101089,0.0001400073,0.0004812925,0.0001635322,0.0001371803,0.0002028834,0.0003951012,0.0005110528,0.00009459187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002821099,"about_ca_system_score_gemma":0.0004754639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007009303,"about_ca_topic_score_gemma":0.01049206,"domain_scores_codex":[0.9998937,0.00003601192,0.0000079062,0.00002794541,0.00001429144,0.00002020329],"domain_scores_gemma":[0.9998657,0.00006430363,0.00001467608,0.00000955542,0.0000305297,0.00001529175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009762453,0.0006702537,0.09830453,0.000227362,0.0005158842,0.0007232561,0.0003697305,0.2461672,0.04611351,0.002982184,0.004486985,0.5984628],"study_design_scores_gemma":[0.00001393014,0.00009203305,0.009233355,0.00001322044,0.00003162623,0.0001200321,0.00002727485,0.9870431,0.001930698,0.001198279,0.0002854862,0.00001106528],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4948582,0.0011798,0.5004225,0.0006610579,0.00006186739,0.0001347056,0.0005641977,0.000564712,0.001552947],"genre_scores_gemma":[0.9388418,0.0002296628,0.05955338,0.0001244468,0.0000192944,0.00004673636,0.000401649,0.00001411436,0.0007688424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007009303,"threshold_uncertainty_score":0.013937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02336891867767902,"score_gpt":0.2966399683191505,"score_spread":0.2732710496414714,"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."}}