The title of the research paper is heart disease detection and real time monitoring using a wearable Device (smartwatch)

the main objective is to develop an machine learning model and integrate it with a smart watch with an embedded API for the prediction, detection and real-time monitoring of heart disease patients.

The study is the integration of machine learning and artificial intelligence by the use of IoT , it combines machine learning, healthcare informatics and cardiovascular health. within machine learning, the utilization of various algorithms such as regression, decision tree, random forest and deep learning techniques are used for predictive modelling. These algorithms leverage diverse features extracted from patient data to classify individuals into different risk categories.

After model training, the model is deployed in a smartwatch, whereby the smartwatch not only monitors the patient vitals, but is able to make predictions of possible heart disease according to the readings and patients history data, by looking at different risk factors. the model is also able to detect when the patient is about to have a heart attack , which then triggers an alert system which sends an alert message to a specified guardian/ medical practitioner. By doing so, it allows timely intervention of heart disease patients, so that they can get help in time, thus also reducing mortality rate due to CVD