A Bayesian Inference Based Computational Tool for Parametric and Nonparametric Medical Diagnosis

This software tool employs Bayesian inference to calculate the posterior probability of a disease diagnosis. It comprises three distinct modules, each designed to allow users to define and compare parametric and nonparametric distributions. The tool i analyzes datasets generated from two separate diagnostic tests, each performed on both diseased and nondiseased populations. The provided datasets, d1 (Fasting Plasma Glucose (mg/dl) in diabetics), d2 (Glycated Hemoglobin A1c (%) in diabetics), nd1 (Fasting Plasma Glucose (mg/dl) in nondiabetics), and nd2 (Glycated Hemoglobin A1c (%) in nondiabetics), were obtained from the database of the National Health and Nutrition Examination Survey (NHANES), Centers for Disease Control and Prevention, USA. They can be replaced by other datasets of two measurands in diseased and nondiseased populations.Bayesian Diagnosis can be run on Wolfram Player® or Wolfram Mathematica