Report Generation on ECGs Survey Data Analysis Using Threshold Based Inference Engine

Autor: Shoab Ahmad Khan, Saria Safdar, Fahim Arif
Rok vydání: 2012
Předmět:
Zdroj: International Journal of Information and Education Technology. :265-269
ISSN: 2010-3689
Popis: 265  Abstract—Heart diseases and strokes are considered as number one killer as they account for around 35 to 40 per cent of the total disease burden in Pakistan. The ratio of heart patients is increasing day by day, which is an alarming condition for the country. This situation needs a detailed analysis which can show the geographical distribution of heart patients and also the city wise attributes (age, weight, income etc) that are aggregating more in the heart disease. A Threshold Based Inference Engine is designed which infers the knowledge base by generating the association rules on each city. These rules infer the clustered data to extract the city wise more risk increasing attributes, and the common disease in that city. Automated Minnesota code is used for the verification of the collected ECGs. The results show that Threshold based Inference Engine successfully and efficiently generates a detailed report of each city including more diseased people and highlights the attributes increasing the risk factor. The analysis will highlight geographical areas with maximum disease and the attributes (weight, age, income, drugs etc) contributing more in the heart disease in the particular area. The generated report will provide great benefit for use by Health Organization and international health organization like ministry of health and WHO. The paper is organized as follows: section 1 describes the introduction, section 2 is literature survey, section 3 is the technique description and section 4 is the conclusion and future work.
Databáze: OpenAIRE