The impact of machine learning models in reducing variants of uncertain significance (vus) for individuals from underrepresented populations who are undergoing testing for inherited metabolic disorders

This chapter is dedicated to study the neutrosophic probability distribution functions by using the concept of algebraic AH-isometry. This work provides an easy approach to compute and define probability distribution functions and cumulative distribution functions of common distributions and their characteristic measures such as expectation, variance, and standard deviation. Defining such distributions is very important in modeling, simulation, and forecasting. Also, it opens the way to define robust statistical tests which is very important in medical and biological applications. Many examples of modeling bio-applications are presented.