Optimized Predictive Models in Health Care Using Machine Learning

10Optimizing Prediction of Liver Disease Using Machine Learning Algorithms

Rachna¹, Tanish Jain², Deepak Shandilya²* and Shivangi Gagneja²

¹Department of Computer Science and Engineering, Sonipat, India

²Department of Computer Science and Engineering, Mohali, India

Abstract

On the right side of the abdomen, directly behind the ribs, is an organ called the liver, located just under the ribs on the right side of the stomach. It is essential for the body’s detoxification process and the digestion of meals. Viruses, drinking alcohol, and being overweight can all cause liver disorders. The consequences of liver disorders vary based on the root cause of liver problems and can get worse if not diagnosed early. Based on symptoms, including yellowing of the skin and eyes, abdominal discomfort and swelling, and dark urine color. Researchers use machine learning to help them identify and categorize liver problems. Yet, missing values in medical data may lead to imbalanced study conclusions and make it challenging to forecast and assess the data. Therefore, to increase prediction accuracy and reduce overfitting, employ an algorithm like random forest, which utilizes averaging several decision tree classifiers to different attributes of the liver disorder dataset. The overall performance was improved to 73.3% after multiple simulations and the input of inconsistencies. As a result, this approach could be used to identify illnesses using more detailed clinical information.

Keywords: Liver ...