BIOSTATISTICAL MODELS FOR PREDICTING NUTRITIONAL OUTCOMES

Abstract

We are going to talk about dietary patterns analysis in this article on biostatistical models for predicting nutritional results. Some of the conventional techniques for identifying dietary trends are Dietary Quality Scores, Principal Component Analysis (PCA), Factor Analysis, Clustering Analysis, and Reduced Rank Regression. The Finite Mixture Model, Treelet Transform, and Data Mining are a few cutting-edge techniques that demand consideration. The available data and research topics determine the method to be used. These models seek to ascertain the body's nutritional needs and comprehend variations in those needs amongst organs and the body as a whole. They give the need for micronutrients a logical foundation. It also provides information on how to apply and utilize dietary pattern analysis. This progress is summarized in this abstract