{"id":"W4296466187","doi":"10.18280/mmep.090423","title":"Model Based Risk Assessment to Evaluate Lung Functionality for Early Prognosis of Asthma Using Neural Network Approach","year":2022,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Quality and Safety in Healthcare","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Spirometry; Generalization; Computer science; Population; Radial basis function; Asthma; Machine learning; Artificial intelligence; Lung function; Support vector machine; Statistics; Medicine; Mathematics; Lung; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003792027,0.0001945269,0.0004393603,0.00008044953,0.0009137553,0.00001334761,0.0001272615,0.0001067771,0.00002430874],"category_scores_gemma":[0.00008541415,0.000185923,0.0001064441,0.0002303887,0.00001888056,0.00006207204,0.000124307,0.0006755019,6.091407e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001693974,"about_ca_system_score_gemma":0.0001431018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008513124,"about_ca_topic_score_gemma":7.66567e-7,"domain_scores_codex":[0.9975284,0.0003178345,0.0008231764,0.0003428655,0.0004295412,0.0005582357],"domain_scores_gemma":[0.9984176,0.0008041453,0.0001889028,0.0002360918,0.0001670134,0.0001862309],"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":[0.0000559,0.00009665997,0.001415981,0.004383342,0.00003278985,9.378761e-8,0.001643969,0.9800092,0.00001310577,0.012219,0.00002689998,0.0001030326],"study_design_scores_gemma":[0.0004343732,0.0001279127,0.0001814507,0.0002649033,0.00006025392,7.871913e-7,0.0001570875,0.9839303,8.407812e-7,0.01461571,0.0000420474,0.0001843574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2668064,0.00006798318,0.7310297,0.0002670439,0.0001148262,0.001498505,0.00008241541,0.00007767597,0.00005543411],"genre_scores_gemma":[0.6801501,0.000002612411,0.3184311,0.00007969025,0.00006735029,0.001191995,0.00001905347,0.0000332,0.00002489955],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4133437,"threshold_uncertainty_score":0.7581719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1920025869887789,"score_gpt":0.399972301151058,"score_spread":0.2079697141622791,"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."}}