Clinical ML — AI Drug & Diet Recommendation System
TL;DR
The ClinicalML uses advanced machine learning algorithms to analyze patient data and identify health conditions accurately using important parameters like age, BMI, blood pressure, and glucose levels to assist in early disease prediction and personalized treatment support.
Abstract
The ClinicalML is an artificial intelligence-based healthcare system designed to assist in early disease prediction and personalized treatment support. It uses advanced machine learning algorithms to analyze patient data and identify health conditions accurately. The system focuses on common diseases such as diabetes, hypertension, and cardiovascular disorders using important parameters like age, BMI, blood pressure, and glucose levels. ClinicalML follows a two-stage approach in which Random Forest, Gradient Boosting, and Multi-Layer Perceptron (MLP) models are combined using a soft voting ensemble method for accurate disease classification. Based on the predicted disease, the system provides personalized diet plans and medication schedules. The complete system runs within a web browser without requiring backend servers or cloud infrastructure, ensuring faster processing, better privacy, and easy accessibility. ClinicalML also includes charts and graphs to help users and doctors understand the results and make informed healthcare decisions quickly. Keywords: AI in Healthcare, Disease Prediction, Diet & Drug Recommendation, Random Forest, Gradient Boosting, Multi-Layer Perceptron, Soft Voting Ensemble