کنفرانس بین المللی کنترل ، ابزار دقیق و اتوماسیون

صفحه اصلی / نهمین کنفرانس بین المللی کنترل ، ابزار دقیق و اتوماسیون

Machine Learning-Based Prediction of Coronary Heart Disease

نویسندگان :

Badrosadat Nategholeslam Shirazi¹ Shiva Naghsh² Ali Akbar Safavi³ Amir Sharafkhaneh⁴

1- دانشگاه شیراز 2- دانشگاه شیراز 3- دانشگاه شیراز 4- Baylor College of Medicine, Houston, TX, USA

کلمات کلیدی :

Coronary Heart Disease،Machine learning،Risk prediction

چکیده :

Coronary Heart Disease (CHD) remains a significant global health concern. This study utilizes the Sleep Heart Health Study (SHHS) dataset, encompassing demographic features, measurement features, and combination of these two categories, to develop a predictive model for CHD risk. The Multi-Layer Perceptron (MLP) neural network is employed to capture intricate relationships within the data. An accuracy mostly greater than 70% in CHD risk prediction is exhibited by the MLP model when categories of selected features are fed to it. This research emphasizes the importance of using readily available data for physicians and advanced machine learning technique to enhance early CHD risk prediction. These findings have the potential to improve personalized medicine and targeted interventions for CHD prevention and management.