Blog: Fuzzy Thinking Could Spot Heart Disease Risk

Fuzzy Thinking Could Spot Heart Disease Risk
ScienceDaily (09/16/10)

Anna University's Khanna Nehemiah and colleagues have used fuzzy logic, a neural network computer program, and genetic algorithms to create a medical diagnostic system for predicting the risk of cardiovascular disease in patients. They employed fuzzy logic to teach a neural network to examine patient data and identify correlations that would indicate a person's risk factor. The medical diagnostic system has produced a statistical model that improves on previous efforts and is accurate 90 percent of the time in determining patient risk, according to the researchers. "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," according to the researchers. They say the new model addresses all of these points. The fuzzy neural network could be further enhanced by modifying its architecture, and by extracting generic rules to find a more precise risk factor.

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