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
Metadata
| Item Type: | Article |
|---|---|
| Creators: | Creators Email / ID Num. Suhaidin, Muhammad Iqbal 2021886804@student.uitm.edu.my Mohamed Yusoff, Syarifah Adilah syarifah.adilah@uitm.edu.my Johan, Elly Johana ellyjohana@uitm.edu.my Mydin, Azlina azlin143@ uitm.edu.my Wan Mohamad, Wan Anisha wannan122@ uitm.edu.my |
| Contributors: | Contribution Name Email / ID Num. Advisor Kadar, Rozita UNSPECIFIED Chief Editor Othman, Jamal UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Evolutionary programming (Computer science). Genetic algorithms |
| Divisions: | Universiti Teknologi MARA, Pulau Pinang > Permatang Pauh Campus |
| Journal or Publication Title: | Enhancing Innovations In e-Learning For Future Preparation |
| ISSN: | 978-967-25608-8-3 |
| Volume: | 5 |
| Page Range: | pp. 51-56 |
| Keywords: | Heart Disease, Random Forest Algorithm, Classification Algorithm, Prediction Analysis |
| Date: | April 2023 |
| URI: | https://ir.uitm.edu.my/id/eprint/83497 |
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