Key result
Enhanced machine learning classification algorithms achieve high accuracy for diagnosing heart disease.
Why the study?
Heart disease remains one of the leading causes of mortality worldwide, motivating enhanced methods for accurate diagnosis.
An enhanced machine learning approach using classification algorithms demonstrates high accuracy for early heart disease detection.
Should not alter clinical practice; leaves open prospective validation of ML for heart disease detection.
Heart disease remains one of the leading causes of mortality worldwide. This study presents an enhanced machine learning approach for accurate heart disease diagnosis using classification algorithms. The dataset was preprocessed and analyzed to improve prediction performance. Experimental results demonstrate that the proposed approach achieves high accuracy and can assist healthcare professionals in early disease detection. The findings indicate the effectiveness of machine learning techniques in supporting clinical decision-making.
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Arpita Raykar (2026) studied Heart disease. Enhanced machine learning approach was evaluated on Prediction performance and accuracy. An enhanced machine learning approach using classification algorithms achieved high accuracy for heart disease diagnosis, demonstrating effectiveness in supporting clinical decision-making.
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