{"id":"W4311358350","doi":"10.5539/cis.v16n1p39","title":"CNN Model for Sleep Apnea Detection Based on SpO2 Signal","year":2022,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Softmax function; Computer science; Polysomnography; Convolutional neural network; Deep learning; Sleep apnea; Apnea; Artificial intelligence; SIGNAL (programming language); Pattern recognition (psychology); Pooling; Medicine; Speech recognition; Cardiology; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0001642548,0.0006519196,0.0002999413,0.000339528,0.0001480148,0.000322841,0.0006923866,0.0004533406,0.002351175],"category_scores_gemma":[0.0004336929,0.0002303764,0.0005615191,0.0002300871,0.0001200125,0.0003926757,0.0002342169,0.0005274327,0.0005574899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005708688,"about_ca_system_score_gemma":0.0005724456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02271358,"about_ca_topic_score_gemma":0.01912126,"domain_scores_codex":[0.9999335,0.000005623586,0.00000462754,0.00002361133,0.00001596921,0.00001667458],"domain_scores_gemma":[0.9999164,0.00001699367,0.000009502125,0.000006606279,0.00004514142,0.00000524045],"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":[0.00036237,0.00017699,0.00764744,0.0001407176,0.0001866624,0.0002688041,0.00004738673,0.7032486,0.0220815,0.002309559,0.006766181,0.2567639],"study_design_scores_gemma":[0.000003080145,0.00002200535,0.0006878888,0.000004320536,0.00001346803,0.00001557996,0.000001846429,0.9975235,0.00117193,0.0001964033,0.0003567811,0.000003123487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2899549,0.004086919,0.6803414,0.001199766,0.0007491834,0.0001601432,0.002370731,0.005109155,0.01602792],"genre_scores_gemma":[0.9431569,0.001044278,0.03900776,0.0002203382,0.00007273658,0.0001101476,0.001645443,0.00005771832,0.01468461],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02271358,"threshold_uncertainty_score":0.04516274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256806930249321,"score_gpt":0.2843645437115557,"score_spread":0.2617964744090625,"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."}}