ABSTRACT
Embark on a transformative journey into the intersection of healthcare and data science with our innovative project, “Prediction of Liver Disorders using Machine Learning Algorithms: A Comparative Study.” This abstract extends an insightful invitation to students eager to explore the application of machine learning in the diagnosis and prediction of liver disorders, unraveling the nuances of diverse algorithms through a comparative lens.
In this project, we navigate the complex landscape of medical data, employing various machine learning algorithms to predict and classify liver disorders. Students will be introduced to the fundamental concepts of healthcare analytics, feature engineering, and the practical application of machine learning techniques in the context of predictive medicine.
This abstract provides a glimpse into the core principles of our project, showcasing a comparative analysis of machine learning algorithms in terms of accuracy, sensitivity, and specificity for predicting liver disorders. Through hands-on exploration, students will gain a nuanced understanding of the strengths and limitations of different algorithms, empowering them to contribute to advancements in medical diagnostics.
