Article,
Identification and alertness of cardiovascular disease using MATLAB with IoT
BOHR International Journal of Research on Cardiology and Cardiovascular Diseases, 1 (1): 31-35 (2023)
DOI: 10.54646/bijrccd.2023.05
Abstract
The last several decades have seen cardiovascular illnesses become the leading cause of mortality globally, inboth industrialized and developing nations alike. Clinical staff monitoring and early diagnosis of heart disorderscan both lower death rates. However, because it takes more intelligence, time, and skill, precise cardiac diseaseidentification in every case and 24-h patient consultation by a doctor are not yet possible. With the use of machinelearning techniques, a preliminary concept for a cloud-based system to predict heart disease has been put out inthis study. An effective machine-learning strategy should be applied for the precise identification of cardiac illness.This method was created after a thorough comparison of many machine learning methods in MATLAB coding. Theapplication may thus be utilized by the medical professionals to monitor the patient’s real-time sensor data andbegin live video streaming if urgent care is necessary. The ability of the suggested method to notify both partiesright away when the patient checks the stage while the doctor isn’t there was a crucial component.
