Inflammation of Liver and Hepatitis Disease Prediction using Machine Learning Techniques

• Main Authors: Swetha, K., Kiran, Ajmeera, Pavanam, Keerthi, Vijaya Kumari, E.N., Naresh, Thummala, Baba, Mohammad Jahangeer
• Format: Conference Proceeding
• Language: English
• Subjects: AI(Artificial Intelligence); ANN (Artificial Neural Networks); Artificial neural networks; KNN (K-Nearest Neighbor); Liver diseases; Machine learning; Machine learning algorithms; Medical services; ML (Machine Learning); Predictive models; Support vector machines; SVM(Support Vector Machine); UML(Unified Modelling Language)
• ISSN: 2768-5330
• DOI: 10.1109/ICICCS56967.2023.10142912

This research study intends to design a novel system for the detection and diagnosis of hepatitis disease. It has become necessary to integrate AI with healthcare, as it helps in the detection of diseases in an earlier phase before it deteriorates the body. This unpredictable disease can worsen the situation of the human body if it is not diagnosed properly. In this work, a brief study between machine learning algorithms were performed and algorithms like Support Vector Machine, K-Nearest Neighbor, and Artificial Neural Network were considered for classifying the data points into relevant classes, and for the prediction and diagnosis of hepatitis. The diagnosis of hepatitis is a hectic and expensive task as it involves many tests and parameters to consider. A system which is well trained with efficient data can be useful in real life, so that diagnosis of hepatitis can be performed at the ease of home.