A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues
Journal: Molecules
Year: 2020

Metals are considered to be one of the most hazardous substances due to their potential for accumulation, magnification, persistence, and wide distribution in water, sediments, and aquatic organisms. Demersal fish species, such as turbot (<i>Psetta maxima maeotica</i>), are accepted by the scientific communities as suitable bioindicators of heavy metal pollution in the aquatic environment. The present study uses a machine learning approach, which is based on multiple linear and non-linear models