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

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

DOI: 10.2174/9781681089553122010010

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

Pp: 123-140 (18)

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Abstract

SHS investigation development is considered from the geographical and historical viewpoint. 3 stages are described. Within Stage 1 the work was carried out in the Department of the Institute of Chemical Physics in Chernogolovka where the scientific discovery had been made. At Stage 2 the interest to SHS arose in different cities and towns of the former USSR. Within Stage 3 SHS entered the international scene. Now SHS processes and products are being studied in more than 50 countries.

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.

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