Analysis of ECGs Survey Data Using Threshold Inference Engine

Authors

  • Author papers Institute of Information System & Research Cent
  • Saria Safdar Military College of Signals (MCS), NUST, Islamabad
  • Shoab Ahmad Khan NUST, Islamabad
  • Fahim Arif NUST, Islamabad

Keywords:

Aggregation, Cardiac Arrhythmias, Centroid, ECG, Fuzzification, Inference Engine, Membership

Abstract

Cardiovascular diseases are increasing day by day in Pakistan and now reach to a ratio of around 35 to 40 per cent of the total disease burden in Pakistan. This increasing ratio needs a detailed analysis of the overall geographical distribution of heart patients and also the most aggregating attributes (age, weight, income etc). To cater this situation a Threshold Inference Engine is designed which generates the association rules to extract the city wise more risk increasing attributes, and the common heart disease in that city. Automated Minnesota code is used for the verification of the collected ECGs. The generated results of the
Threshold Inference Engine successfully and efficiently generate a detailed report of each city describing the common heart disease and the attributes

Author Biography

Shoab Ahmad Khan, NUST, Islamabad

Computer Engineering Department
Electrical and Mechanical Engineering (EME), 

References

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Published

2020-08-30

How to Cite

papers, A., Safdar, S. ., Khan, S. A. ., & Arif, F. (2020). Analysis of ECGs Survey Data Using Threshold Inference Engine. International Journal on Information Technology and Computer Science, 4(1). Retrieved from http://ijitcs.info/index.php/ijitcs/article/view/10

Issue

Section

Research Articles

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