Rx Assist : Smart Disease Prediction and Drug Recommendation
Loading...
Files
Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
NHCE
Abstract
Rx Assist represents a state-of-the-art healthcare solution aimed at improving medical decision-making and patient care through advanced machine learning techniques. This sophisticated system features two main components: disease prediction and drug recommendation. By evaluating patient data such as symptoms, age, and gender, Rx Assist employs various machine learning models, including Gaussian Naive Bayes, Random Forest, Logistic Regression, and Sklearn Decision Tree, to provide highly precise predictions. A distinctive aspect of the system is its majority voting mechanism, which effectively addresses complex symptom presentations and overlapping diseases, thereby enhancing diagnostic accuracy. The drug recommendation component utilizes a meticulously curated dataset along with machine learning algorithms to propose personalized medication options tailored to individual patient characteristics, including specific disease profiles. To further enhance user engagement, Rx Assist offers user-friendly interfaces for both patients and healthcare providers, featuring capabilities such as appointment scheduling, comprehensive access to patient data, and customized treatment plans. By addressing shortcomings in conventional healthcare systems, Rx Assist fosters effective communication between doctors and patients, ensures efficient healthcare delivery, and establishes a foundation for future developments in personalized medicine. This groundbreaking system not only enhances diagnostic precision and treatment results but also optimizes healthcare workflows, setting a new benchmark for intelligent healthcare solutions