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

Authors: Chatzimichail Theodora; Hatjimihail Aristides;

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

Abstract

This software tool employs Bayesian rule 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 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 20-40 years old), d2 (Glycated Hemoglobin A1c (%) in diabetics 20-40 years old), nd1 (Fasting Plasma Glucose (mg/dl) in nondiabetics 20-40 years old), and nd2 (Glycated Hemoglobin A1c (%) in nondiabetics 20-40 years old), 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®

Related Organizations
Keywords

Diabetes mellitus, Parametric Distribution, Nonparametric Distribution, Probability Density Function, Copula Distribution, Bayesian Inference, Likelihood, Kernel Density Estimator, Bayesian Diagnosis, Prior Probability, Posterior Probability

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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