{"id":"W4387571292","doi":"10.3390/diagnostics13203187","title":"Prediction of the Sleep Apnea Severity Using 2D-Convolutional Neural Networks and Respiratory Effort Signals","year":2023,"lang":"en","type":"article","venue":"Diagnostics","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; National Institute on Aging; University of California, Davis; Agencia Estatal de Investigación; Johns Hopkins University; Instituto de Salud Carlos III; Universidad de Valladolid; National Institutes of Health; Case Western Reserve University; European Regional Development Fund; University of Washington; York University; University of Minnesota","keywords":"Polysomnography; Central sleep apnea; Apnea; Sleep apnea; Intraclass correlation; Medicine; Convolutional neural network; Mean squared error; Hypopnea; Sleep (system call); Apnea–hypopnea index; Statistics; Computer science; Artificial intelligence; Internal medicine; Mathematics; Reproducibility","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":[0.000423708,0.000846984,0.0003322613,0.000607402,0.0001204089,0.0003862873,0.0003354979,0.0004715489,0.0006169931],"category_scores_gemma":[0.001161489,0.0002803096,0.0004925559,0.0002765099,0.0001421599,0.0002783243,0.0003598378,0.000417621,0.0001614353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004877181,"about_ca_system_score_gemma":0.0003935172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01419697,"about_ca_topic_score_gemma":0.01609771,"domain_scores_codex":[0.9998747,0.00001967015,0.000009374118,0.00004969063,0.00001958809,0.00002695914],"domain_scores_gemma":[0.9997367,0.0001300232,0.0000397665,0.0000142096,0.00006354688,0.00001568484],"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":[0.000733408,0.0004409112,0.08768409,0.0001264679,0.0003024852,0.0003472446,0.00009411843,0.6437944,0.0277491,0.0006032654,0.001660629,0.236464],"study_design_scores_gemma":[0.000003153446,0.00002567772,0.00694383,0.000004896787,0.00001374748,0.00001951168,0.000004701947,0.9916488,0.001168873,0.00009832149,0.00006424056,0.00000421869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8483248,0.001047416,0.1471112,0.0002327066,0.0001276492,0.0000659344,0.000783483,0.0006277381,0.001679048],"genre_scores_gemma":[0.9856735,0.0001771015,0.01272266,0.00004177084,0.00001804894,0.0000264703,0.0004364648,0.0000102085,0.0008937078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01419697,"threshold_uncertainty_score":0.02822864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04988190636213338,"score_gpt":0.3002375872165076,"score_spread":0.2503556808543743,"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."}}