Enhancing Heart Disease Prediction Using CardiAI: With Key Performance Metrics Accuracy, Precision, Recall and F1-Score

Authors

  • Asish Tony Mulaguri Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
  • Sai Krishna Katta Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
  • Venkata Kousik Karanam Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
  • Yellamma Pachipala Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
  • Sriyaa Narisety Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India

Keywords:

CardiAI, deep learning, heart disease prediction, logistic regression, SVC, K – nearest Neighbours, accuracy, healthcare, early diagnosis, artificial intelligence, patient management, predictive modelling

Abstract

In this study, we introduce CardiAI, a pioneering deep learning algorithm meticulously crafted for precise heart disease prediction. Unlike existing models, CardiAI's innovation lies in its intricate architecture, integrating strategic dropout layers, early stopping mechanisms, and sophisticated techniques to mitigate overfitting. Our extensive comparative analysis showcases CardiAI's exceptional performance, surpassing traditional models such as support vector regression, logistic regression, and k-nearest neighbours. Demonstrating unparalleled accuracy without compromising efficiency, CardiAI achieves remarkable predictive rates, signifying a significant advancement in heart disease diagnostics. This research presents a transformative leap in cardiovascular healthcare, offering a more accurate and efficient predictive model that facilitates early disease detection and informed patient management. The breakthrough potential of CardiAI stands poised to revolutionize medical diagnostics, promising to significantly improve patient outcomes while optimizing healthcare resources.

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Published

24.03.2024

How to Cite

Mulaguri, A. T. ., Katta, S. K. ., Karanam, V. K. ., Pachipala, Y. ., & Narisety, S. . (2024). Enhancing Heart Disease Prediction Using CardiAI: With Key Performance Metrics Accuracy, Precision, Recall and F1-Score. International Journal of Intelligent Systems and Applications in Engineering, 12(18s), 646–655. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5013

Issue

Vol. 12 No. 18s (2024)

Section

Research Article

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