Disease Prediction Based on Symptoms and Drug Recommendation

Within the sphere of healthcare, the widespread employment of large datasets has infiltrated each element of the field, starting from groundbreaking scientific inquiry right through to optimizing patient interactions and therapeutic results. With a myriad of diverse ailments challenging healthcare systems worldwide, the integration of Machine Learning and Big Data technologies has emerged as a novel approach to disease prediction and diagnosis. This research embarks on a transformative journey, investigating the application of machine learning algorithms to forecast diseases based on presenting symptoms and provide drug recommendation. Through the implementation of Naive Bayes, Decision Trees, Random Forests, and Logistic Regression, this study explores the path to more accurate and data-driven healthcare solutions.