Bayesian rule modeling for interpretable mortality classification of covid-19 patients

HIGHLIGHTS

• who: Myung-Mook Han from the Software Department, Gachon University, Seongnam, Korea have published the Article: Bayesian Rule Modeling for Interpretable Mortality Classification of COVID-19 Patients, in the Journal: (JOURNAL) of January/10,/2020
• what: The authors focused on dependency reduction using partial correlation and mutual information. This model provided rules of "if antecedent then results, posterior probability(θ)". The results confirmed that the model had better performance than a previously published model . Compared to another study that used a fuzzy rule list , the model showed a 3.3% lower AUC score for the validation . . .
  

   

  

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