{"id":"W2903672000","doi":"10.1371/journal.pone.0209018","title":"Mucopolysaccharidosis type II detection by Naïve Bayes Classifier: An example of patient classification for a rare disease using electronic medical records from the Canadian Primary Care Sentinel Surveillance Network","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Queen's University","funders":"Shire Canada","keywords":"Naive Bayes classifier; Bayes' theorem; Mucopolysaccharidosis type II; Classifier (UML); Bayesian network; Artificial intelligence; Categorical variable; Disease; Medicine; Machine learning; Medical record; Computer science; Bayesian probability; Internal medicine; Enzyme replacement therapy; Support vector machine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00363945,0.0007850463,0.0007898998,0.001786839,0.0009650706,0.0008906116,0.001006311,0.0009251314,0.0008241621],"category_scores_gemma":[0.01065264,0.0001920959,0.0007514807,0.001436308,0.0003123111,0.0003478442,0.0003897034,0.0007217935,0.0003291219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002579046,"about_ca_system_score_gemma":0.003858791,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4194068,"about_ca_topic_score_gemma":0.4085499,"domain_scores_codex":[0.998139,0.0004914052,0.0001853595,0.0004175823,0.0005607145,0.0002059553],"domain_scores_gemma":[0.9953877,0.002561308,0.0002235335,0.0002888794,0.001375112,0.0001634394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001138535,0.0006099297,0.5988585,0.0006080109,0.0004442124,0.002200003,0.0008783985,0.07300377,0.004012271,0.001687589,0.02270406,0.2938548],"study_design_scores_gemma":[0.0001419177,0.0002844981,0.1361732,0.0001782836,0.0002028436,0.001017054,0.0009215595,0.844426,0.005020697,0.003479059,0.008042754,0.0001120838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9202689,0.001460608,0.05711925,0.001840783,0.0002048766,0.0007679694,0.01371866,0.0011,0.003518893],"genre_scores_gemma":[0.903523,0.0003718594,0.08164031,0.0003021642,0.00005866,0.0001520647,0.01285933,0.0000313038,0.001061333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5805932,"threshold_uncertainty_score":0.8339312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06430013897306643,"score_gpt":0.2448939243251619,"score_spread":0.1805937853520955,"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."}}