Early detection of heart disease using Random Forest Algorithm / Muhammad Iqbal Suhaidin ... [et al.]

Suhaidin, Muhammad Iqbal and Mohamed Yusoff, Syarifah Adilah and Johan, Elly Johana and Mydin, Azlina and Wan Mohamad, Wan Anisha (2023) Early detection of heart disease using Random Forest Algorithm / Muhammad Iqbal Suhaidin ... [et al.]. Enhancing Innovations In e-Learning For Future Preparation, 5. pp. 51-56. ISSN 978-967-25608-8-3
Abstract

The prediction of heart diseases is a crucial aspect of healthcare, as it helps medical professionals to diagnose and treat the condition at an early stage. This is a preliminary study that aims to investigate the Random Forest Algorithm (RFA) that accurately predicts the presence of heart diseases, enabling healthcare providers to take proactive measures to prevent severe health complications and improve patient outcomes. RFA as a machine learning classification model has the potential to provide more accurate predictions than traditional methods. This potential has been investigated by thoroughly compared with several other studies across implementation of different types of dataset and algorithms. Furthermore, additional prototypes could be used in clinical settings, providing valuable insights to healthcare providers and contributing to the advancement of medical research

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