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

ABSTRACT: Medical diagnosis is the basis for treatment and management decisions in healthcare. Conventional methods for medical diagnosis commonly use established clinical criteria and fixed numerical thresholds. The limitations of such an approach may result in a failure to capture the intricate relations between diagnostic tests and the varying prevalence of diseases. To explore this further, we have developed a freely available specialized computational tool that employs Bayesian inference to calculate the posterior probability of disease diagnosis. This novel software comprises of three distinct modules, each designed to allow users to define and compare parametric and nonparametric distributions effectively. The tool is equipped to analyze datasets generated from two separate diagnostic tests,

SUBMITTER: Chatzimichail T 

PROVIDER: S-EPMC10572594 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature