{"id":"W3196700564","doi":"10.1145/3472163.3472175","title":"Explainable Data Analytics for Disease and Healthcare Informatics","year":2021,"lang":"en","type":"article","venue":"","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Computer science; Data science; Interpretability; Big data; Analytics; Health informatics; Informatics; Data analysis; Health care; Component (thermodynamics); Variety (cybernetics); Disease; Data modeling; Data mining; Artificial intelligence; Medicine; Database; Engineering","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":[0.005289554,0.001493934,0.00113774,0.004773213,0.0006922008,0.003546706,0.002501806,0.001727678,0.006006584],"category_scores_gemma":[0.02359894,0.0006299426,0.002049324,0.004677636,0.001355248,0.006931098,0.004125138,0.003168608,0.002074404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001577153,"about_ca_system_score_gemma":0.002005663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004599121,"about_ca_topic_score_gemma":0.003456628,"domain_scores_codex":[0.9955925,0.0014789,0.0004848485,0.0008277979,0.001478201,0.0001377289],"domain_scores_gemma":[0.9811091,0.01077584,0.001383626,0.004755125,0.001655994,0.0003203208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005056916,0.0002857256,0.01278786,0.002000133,0.0005965924,0.0008369758,0.001753072,0.04250952,0.007310185,0.1245486,0.07252377,0.7343418],"study_design_scores_gemma":[0.0000822681,0.0001063178,0.004269688,0.0006012595,0.000180806,0.0006484152,0.0004905891,0.3884397,0.01102376,0.4414275,0.1525617,0.0001679612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005839608,0.003528069,0.9464421,0.00648284,0.0002051316,0.0003647996,0.005713107,0.02713155,0.004292796],"genre_scores_gemma":[0.1798707,0.004803556,0.7932895,0.002324339,0.0005331211,0.0004628666,0.01526534,0.001181961,0.002268594],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006006584,"threshold_uncertainty_score":0.02797419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09696791973435473,"score_gpt":0.3332649963416341,"score_spread":0.2362970766072794,"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."}}