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In the healthcare industry, machine learning is critical. It's crucial in computer-assisted treatment. Computer-Aided Diagnosis is a rapidly growing and active research area in the pharmaceutical business. The present generation of computer vision experts guarantees improved disease detection and analysis precision. Systems are given the ability to think through learning and producing data. This approach allows computers to learn on their own without having to be explicitly trained by a developer. Machine Learning Algorithms are used to categorize data sets using a variety of methods. They are Reinforcement, Deep Learning, Supervised, Unsupervised, and Semi-Supervised techniques. The main aim of this paper is to give a comparative analysis of supervised learning algorithms in the medicinal area and a few of the techniques utilized as a part of liver disease prediction. |
