Non-Alcoholic Fatty Liver Disease Prediction Using Machine Learning and Deep Learning Techniques

Non-Alcoholic Fatty Liver Disease Prediction Using Machine Learning and Deep Learning Techniques

Authors- Assistant Professor Mrs. Pyla Jyothi, Thummalagunti Vani, Pallantla Saicharan, Peethala Jaswanth

Abstract-The liver is a critical metabolic organ within the human body, performing many necessary biological functions, such as protein synthesis and the creation of many biochemicals required for digestion. It is crucial in the support of nearly all other organs. The most common chronic liver disease is Non-Alcoholic Fatty Liver Disease, estimated to affect nearly one-third of the world’s population. Early diagnosis of the disease is very important since it allows for prompt medical intervention and treatment. This research utilizes machine learning whereby data preprocessing is done by cleaning the data through imputation of missing values and feature and deep learning algorithm selection such as feed forward neural network with several dense layers constructed using TensorFlow and trained on the preprocessed data to predict disease status whose performance is measured using metrics.

DOI: /10.61463/ijset.vol.13.issue1.187