{"id":"W3199697367","doi":"10.1109/mwscas47672.2021.9531784","title":"Long Short Term Memory Based Recurrent Neural Network for Wheezing Detection in Pulmonary Sounds","year":2021,"lang":"en","type":"article","venue":"","topic":"Phonocardiography and Auscultation Techniques","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Long short term memory; Mel-frequency cepstrum; Recurrent neural network; Computer science; Multilayer perceptron; Speech recognition; Artificial neural network; Artificial intelligence; Classifier (UML); Pattern recognition (psychology); Term (time); Perceptron; Limit (mathematics); Respiratory sounds; Feature extraction; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002277436,0.0001053487,0.0001939092,0.0001245961,0.00006694297,0.00001828613,0.00003321602,0.00007488565,0.00002863337],"category_scores_gemma":[0.00003779608,0.00009799164,0.0002064032,0.0004220171,0.00002080314,0.00009149426,0.00001433491,0.0001474452,7.042555e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000447626,"about_ca_system_score_gemma":0.00004058307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009165648,"about_ca_topic_score_gemma":0.00008450125,"domain_scores_codex":[0.9991733,0.00004265161,0.0002231115,0.0002379037,0.0001181668,0.0002048125],"domain_scores_gemma":[0.9996006,0.0000704602,0.00002619574,0.0001556875,0.00008691028,0.00006016728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004058743,0.0002711239,0.1421967,0.0003091584,0.00006775874,0.0001933341,0.00009511674,0.0004134564,0.06206082,0.00002647987,0.0008448263,0.7931154],"study_design_scores_gemma":[0.001298556,0.0003653033,0.482316,0.0004780656,0.0001470196,0.0001439223,0.0002652763,0.03753942,0.4754571,0.0005697173,0.001036276,0.000383327],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8653457,0.001124303,0.1261031,0.0004752,0.0005894402,0.0009436899,0.000006490749,0.000428486,0.004983571],"genre_scores_gemma":[0.9944652,0.00004200244,0.00443796,0.0003914171,0.0002398018,0.0001553014,0.00009410956,0.00001483797,0.0001593559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7927321,"threshold_uncertainty_score":0.3995983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02333458305924754,"score_gpt":0.2900392266913062,"score_spread":0.2667046436320587,"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."}}