Fuzzy thinking could spot heart disease risk

Sep 15, 2010

A new approach to evaluating a person's risk of cardiovascular disease, stroke, high blood pressure, or heart failure is reported this month in the International Journal of Data Mining, Modelling and Management. The technique uses fuzzy logic to teach a neural network computer program to analyze patient data and spot correlations that can be translated into a risk factor for an individual.

Khanna Nehemiah of the Anna University Chennai, India, and colleagues have developed a medical diagnostic system for predicting the severity of cardiovascular disease based on combining the fuzzy logic, neural networks and genetic algorithms. The resulting statistical model improves on previous attempts and is accurate 9 times in 10 in determining patient risk.

Cardiovascular disease (CVD) refers to disorders of the heart or blood vessels and includes , cerebrovascular disease, raised blood pressure, , rheumatic heart disease, and . The World Health Organization in 2009 estimated that almost 20 million deaths occur annually from cardiovascular disease and that by 2030 that figure could rise to almost 24 million.

"In order to reduce the rate of morbidity and mortality due to CVD, it is essential to diagnose early and administer appropriate treatment," explains Nehemiah, who points out how clinical diagnosis has always been supported by data analysis combined with medical expertise.

He and his colleagues hope that their new approach to analyzing patient risk will help reduce the time taken by medical experts to make a diagnosis. "A clinical-decision support system should consider issues like representation of medical knowledge, decision making in the presence of uncertainty and imprecision, choice and adaptation of a suitable model," they explain, all points that their new model addresses.

The team concludes that their fuzzy neural network approach could be improved still further by tweaking the architecture of the network and by extracting generic rules from the system that could be used to obtain a more precise risk factor.

Explore further: Big data paves the way for big building and engineering projects

More information: "Fuzzy neuro genetic approach for predicting the risk of cardiovascular diseases" in Int. J. Data Mining, Modelling and Management, 2010, 2, 388-402

Related Stories

New method assesses risks for heart failure patients

Jul 30, 2008

Data from 260 hospitals across the United States has led to the creation of a new method for physicians to more accurately determine the severity of heart failure in patients upon hospital admission, with a goal of reducing ...

Combining medical knowledge to save lives

Jul 09, 2008

European researchers hope to gain more insight into cardiovascular disease by combining clinical, laboratory and metabolic records with genomic data. Cardiovascular disease (CVD) is the biggest killer among chronic diseases, cla ...

Is your heart aging faster than you are?

Nov 26, 2007

Despite the increasing evidence that managing high cholesterol reduces cardiovascular events, many people do not achieve recommended lipid levels. This is due, in part, to patients’ lack of understanding about their risk ...

Recommended for you

Windows Insiders can try out Project Spartan browser

1 hour ago

Microsoft has opened up the (literal) windows, called in creatives, and has been engineering a next-generation browser. Project Spartan is to reflect the general mood of fresh air at Redmond. Although "Project ...

Huawei reports 2014 profit up 33 percent

1 hour ago

Huawei Technologies Ltd., one of the world's biggest makers of telecommunications equipment, said Tuesday its 2014 profit rose 33 percent, helped by strong sales of smartphones.

New taxi app challenges Uber in S.Korea

1 hour ago

South Korea's top mobile messenger operator launched a new web-based cab-hailing service Tuesday to compete with California-based Uber, whose service has been subjected to crackdowns from state regulators.

User comments : 0

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.