Clinical ML — AI Drug & Diet Recommendation System

View at publisher
Authors: G. Vamsi, K. Devendra
Cited by: 1

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

Fields of Study & Subjects

Artificial Intelligence in Healthcare Machine Learning in Healthcare Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
International Scientific Journal of Engineering and Management
Publisher
Edtech Publishers (OPC) Private Limited
Volume
05
Issue
07
Pages
1–9
Publication date
16 July 2026