Key result
An expert system using fuzzy logic to analyze patient data improved the accuracy of detecting heart disease risk levels and supported doctors in providing effective treatment.
Why the study?
High death rates often occur when diseases are not detected early, and automated expert systems may bridge this gap by diagnosing diseases in their initial phases.
Population
Patients evaluated for heart disease risk using data such as age, gender, blood sugar levels, blood…
Design
Other
Authors
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May aid automated risk stratification; leaves open prospective validation before clinical use.
A fuzzy logic-based expert system can automatically analyze patient data to classify heart disease risk and support clinical treatment decisions.
Singh et al. (2024) studied Cardiovascular Disease. Expert system using fuzzy logic was evaluated on Accuracy of detecting heart disease risk levels. An expert system using fuzzy logic to analyze patient data improved the accuracy of detecting heart disease risk levels and supported doctors in providing effective treatment.
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