{"id":"W3197420377","doi":"10.3390/s21175858","title":"An LSTM Network for Apnea and Hypopnea Episodes Detection in Respiratory Signals","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Case Western Reserve University; University of Washington; York University; Johns Hopkins University; National Heart, Lung, and Blood Institute; University of California, Davis; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; University of Minnesota","keywords":"Polysomnography; Hypopnea; Apnea; Sleep apnea; Medicine; Breathing; Apnea–hypopnea index; Obstructive sleep apnea; Computer science; Artificial intelligence; Cardiology; Internal medicine; Anesthesia","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003268335,0.0006768707,0.0002879057,0.0003302207,0.0002431241,0.0004433509,0.0007807837,0.0006319977,0.001873328],"category_scores_gemma":[0.0007461342,0.0002483407,0.0004212172,0.0003859008,0.0001760676,0.0005788615,0.0004261254,0.0008460625,0.00057718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005258234,"about_ca_system_score_gemma":0.0005372685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006827854,"about_ca_topic_score_gemma":0.007654431,"domain_scores_codex":[0.9998589,0.00002482861,0.00001057474,0.00005273459,0.0000273189,0.0000256638],"domain_scores_gemma":[0.9998789,0.00004498158,0.00001396032,0.000008715089,0.00004668205,0.000006693214],"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":[0.0004791081,0.0002297245,0.003968436,0.0002652594,0.0001950612,0.0004043685,0.0001728323,0.4360099,0.04436449,0.002666239,0.006978066,0.5042665],"study_design_scores_gemma":[0.000004083538,0.00005504109,0.0006511604,0.00001369647,0.00002063234,0.00003591083,0.00001184608,0.9945692,0.003236711,0.0008114668,0.0005832818,0.000007016026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1863071,0.00392503,0.7939222,0.0009048691,0.0005893677,0.0001224184,0.001346066,0.005294919,0.007587963],"genre_scores_gemma":[0.9166996,0.0008351225,0.07478302,0.000208977,0.00008782346,0.0001287898,0.001103797,0.00006332435,0.006089565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006827854,"threshold_uncertainty_score":0.01357621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03184273103426783,"score_gpt":0.3230997431848784,"score_spread":0.2912570121506106,"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."}}