10-year risk of future coronary heart disease (CHD) in Patients

Keywords: Prediction, of

Background

The research aims to provide valuable insights for early risk assessment and preventive strategies to reduce CHD incidence. The ANN-based model demonstrates promising accuracy in predicting CHD risk. This study contributes to the field of cardiovascular health by leveraging ANN techniques for improved CHD risk prediction. Assessing the performance of the ANN model requires appropriate evaluation metrics and validation techniques. Determining the accuracy, precision, recall, and other performance measures of the model is crucial for determining its effectiveness in predicting CHD risk. To improve early risk assessment and preventive strategies by providing reliable predictions of future CHD risk. The test loss value of 0.15223607420921326 indicates the average discrepancy between the predicted and actual 10-year risk values. A lower test loss indicates better accuracy in the predictions. The test accuracy of 0.925000011920929 represents the proportion of correctly predicted outcomes compared to the total number of test samples. It indicates that the model achieves a high level of accuracy in estimating the 10-year risk of future CHD in patients.

Aim & Objectives

Aim
To predict the 10-year risk of future coronary heart disease (CHD) in Patients using DL
Objective

Utilize an ANN model to predict the 10-year risk of coronary heart disease (CHD) in patients.
Develop an ANN system that incorporates medical history and risk factors to enhance CHD risk assessment.
Evaluate the ANN's performance in predicting CHD risk, assisting in personalized preventive strategies and healthcare planning.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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