Novel methods for assessing fish blood biochemical data

Abstract

The purpose of this study was the identification and quantification of biochemical parameters over a 1-year cycle and to provide a detailed picture of seasonal changes in plasma metabolites and enzymes. Using the novel methods of machine learning techniques, the authors created and generated for the first time comprehensible classification models for exploring the importance of blood chemistry parameters, strength, mutual interactions or dependencies, and reliability of particular parameters within the seasonal groups.