Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems

Cardiovascular Disease Preventive Prediction and Medication (CVDPPM) - A Model Based on AI Techniques for Prediction and Timely Medical Assistance

Author(s): Y.V. Nagesh Meesala*, Sheik Khadar Ahmad Manoj and Ganapati Bhavana

Pp: 123-140 (18)

DOI: 10.2174/9781681089553122010010

* (Excluding Mailing and Handling)

Abstract

Cardiovascular diseases (CVDs) are the primary cause of death worldwide. If these are not detected early and are not treated on time, one may lose a life. Despite using various measures and standards by doctors, the disease is unpredictable and has a significant death toll. Artificial intelligence (AI) techniques have been introduced to predict the outcome and utilization of machine learning (ML) techniques in diversified areas, showing promising results to make it more sophisticated for both medical professionals and patients. In this chapter, a cardiovascular disease preventive prediction and medication (CVDPPM) model has been developed, which utilizes various communication models for assisting the patients through constant monitoring of heart rate and blood pressure. The main focus of CVDPPM is to predict the early occurrences of artery disease, stroke, and heart failure. It helps notify the nearest cardiologist and medical team with all needed reports for immediate and appropriate medical treatment to save the patient's life. The proposed model fastens the medical procedure by alerting the regular consulted doctor and the family about the patient's condition and medical reports immediately.


Keywords: AI, Cardiologist, Cardiovascular diseases, Cloud storage, CVDPPM, Modeling and training.

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