• Prathmesh Aswar
• Dr.Kavita Joshi
• Mansi Patil
• Vedant Madaghe

Cardiovascular disease (CVD) is a significant contributor to death worldwide, making it important to detect this disease timely and accurately for maintaining health. This study aims to develop automatic models using machine learning in predicting cardiovascular disease (CVD) using real-world clinical data. There are enormous amounts of medical data in the healthcare industry. Machine learning algorithms can help ensure reliable predictions when determining heart diseases. The system uses a variety of sensors including a temperature sensor and blood pressure sensors to monitor physiological signals. In turn, the data is wirelessly sent to a cloud platform where algorithms like Random forest and support vector machine determine early signs of heart disease. The system is implemented as a web-based dashboard which allows the system to be used on multiple platforms.ardiovascular disease (CVD) is one of the leading causes of death worldwide, making early and accurate detection essential for preventive healthcare. The study focuses on developing efficient machine learning-based models for automatic CVD prediction using real-world clinical datasets. The health care industry contains lots of medical data, therefore machine learning algorithms are required to make decisions effectively in the prediction of heart diseases.The system captures physiological signals through various sensors like temperature sensor,blood pressure sensor. The data was transmitted wirelessly to a cloud platform where algorithms like Random Forest and Support Vector Machine were used for early cardiovascular risk detection. The system runs on a web-based dashboard, makes it accessible across different devices. Furthermore, the proposed methodology can be extended to other disease prediction tasks, contributing to the advancement of intelligent healthcare systems.

Cardiovascular Disease, Machine Learning, Explainable AI.

"A Smart Real-Time System for Cardiovascular Risk Prediction using Wearable Sensors, Machine Learning, and Explainable AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 1, page no.c501-c505, January-2026, Available :http://www.jetir.org/papers/JETIR2601260.pdf

"A Smart Real-Time System for Cardiovascular Risk Prediction using Wearable Sensors, Machine Learning, and Explainable AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 1, page no. ppc501-c505, January-2026, Available at : http://www.jetir.org/papers/JETIR2601260.pdf