• Ganesh Khekare
• Akkireddi S V S Rama Prasada Rao
• B R Jagadeeshwar Sai
• Dileep Kumar Reddy

: Heart disease is currently the leading cause of death globally and its prevalence is increasing. Detecting heart disease early is challenging, despite the abundance of data available in clinics and hospitals. However, machine learning has the potential to analyze this data and provide valuable insights, leading to improved decision support systems. Previous research has focused on deep learning techniques, and this study utilizes a Keras-based deep learning model with a thick neural network to accurately diagnose heart problems. The model is evaluated using various combinations of hidden layers and neurons, and the results are measured using sensitivity, specificity, accuracy, and f-measure. The study finds that the proposed deep learning model outperforms individual models and ensemble approaches in terms of accuracy, sensitivity, and specificity across all heart disease datasets that were tested.

Health Insurance, Cardiovascular Disease, Neural Network, Deep Learning, Health Informatics.

"FORECASTING CARDIOVASCULAR HEALTH USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.d567-d579, May-2024, Available :http://www.jetir.org/papers/JETIR2405363.pdf

"FORECASTING CARDIOVASCULAR HEALTH USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppd567-d579, May-2024, Available at : http://www.jetir.org/papers/JETIR2405363.pdf