Heart Disease Prediction Using Neural Network

• Author(s): Shraddha Patel
• Paper ID: 1705467
• Page: 62-67
• Published Date: 02-02-2024
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 7 Issue 8 February-2024

Abstract

Heart disease is a critical health concern worldwide, contributing significantly to morbidity and mortality. Timely prediction and accurate identification of individuals at risk are essential for effective preventive measures and personalized healthcare. In this study, we propose a novel approach for heart disease prediction utilizing a neural network-based model. The neural network is designed to analyze a comprehensive set of input features, including attributes such as blood pressure, cholesterol levels, heart rate, and other characteristic attributes, patients will be categorized based on the different stages of coronary artery disease. The neural network employs advanced deep learning techniques, leveraging its ability to automatically learn intricate patterns and representations from complex datasets. To assess the model's efficacy, extensive experiments are conducted, employing various performance metrics such as accuracy, precision, recall, and area under the receiver operating characteristic curve. In this study, we will be using common Python libraries, such as pandas, matplotlib, sklearn and keras for visualization and implementing deep learning algorithm and also softmax classification function.

Keywords

Neural Network, Deep Learning Techniques, Sklearn, Softmax Classification Function

Citations

IRE Journals:
Shraddha Patel "Heart Disease Prediction Using Neural Network" Iconic Research And Engineering Journals Volume 7 Issue 8 2024 Page 62-67

IEEE:
Shraddha Patel "Heart Disease Prediction Using Neural Network" Iconic Research And Engineering Journals, 7(8)