{"id":"W4381329044","doi":"10.1109/tbme.2023.3287514","title":"Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Machine Intelligence Institute","keywords":"Feature selection; Computer science; Machine learning; Feature (linguistics); Artificial intelligence; Prior probability; Bayesian probability; Artificial neural network; Data mining; Bayesian inference","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.005770532,0.001218857,0.001421331,0.002201262,0.0005363065,0.001349481,0.001588507,0.001258239,0.00183279],"category_scores_gemma":[0.02535503,0.0006920545,0.001004621,0.001053627,0.0009311088,0.001643651,0.001619242,0.003133115,0.0003960965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001563585,"about_ca_system_score_gemma":0.00151888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01164815,"about_ca_topic_score_gemma":0.008635389,"domain_scores_codex":[0.9980825,0.000842833,0.0001407945,0.0004035797,0.0003984057,0.0001319528],"domain_scores_gemma":[0.9882394,0.009435742,0.0008535652,0.0003956498,0.0008582909,0.0002173675],"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":[0.0002617805,0.0000741304,0.007856864,0.0001191973,0.0001212561,0.0001367423,0.0001124429,0.904465,0.0009168109,0.009040372,0.001867592,0.07502775],"study_design_scores_gemma":[0.00001181846,0.00001203161,0.0003958548,0.00001699797,0.00001086864,0.00001675961,0.000007560694,0.9897661,0.0003438974,0.009136918,0.0002713217,0.000009752367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03906593,0.0008421004,0.9568206,0.0006980928,0.00003780371,0.00007511459,0.0005143973,0.000675836,0.001270096],"genre_scores_gemma":[0.8000751,0.0007377911,0.1942329,0.0005420224,0.0001397245,0.0003334895,0.002244954,0.0001726248,0.001521334],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01164815,"threshold_uncertainty_score":0.03051788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03042664565802597,"score_gpt":0.2998549349532155,"score_spread":0.2694282892951895,"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."}}