A group of Indian researchers have conducted a data mining exercise in order to find out important risk factors associated with increasing the chances heart attack in an individual.
The authors after studying the research confirmed that the usual suspects high blood cholesterol, intake of alcohol and passive smoking play the most crucial role in 'severe,' 'moderate' and 'mild' cardiac risks, respectively.
Subhagata Chattopadhyay of the Camellia Institute of Engineering in Kolkata used 300 real-world sample patient cases with different levels of cardiac risk including mild, moderate and severe and mined the data based on twelve known predisposing factors, which included age, gender, alcohol abuse, cholesterol level, smoking (active and passive), physical inactivity, obesity, diabetes, family history, and prior cardiac event.
He then created a risk model that unveiled the specific risk factors associated with heart attack risk.
Chattopadhyay explained that the fundamentals of this work essentially lies in the introduction of clustering techniques instead of purely statistical modeling, where the latter has its own limitations in 'data-model fitting' compared to the former that is more flexible.
He further added that the reliability of the data used, should be examined, and this has been done in this work to enhance its authenticity. I reviewed several papers on epidemiological research, where I'm yet to see these methodologies, used, he said.
The details of study have been published in International Journal of Biomedical Engineering and Technology.
-With inputs from ANI
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