Literatur Review: Klasifikasi Penyakit Jantung Koroner Menggunakan Extreme Learning Machine

Authors

  • Marwan Kosasih Universitas Pamulang
  • Sahrul Ramadhani Universitas Pamulang
  • Arni Susanti Ndruru Universitas Pamulang
  • Reihan Renaldi Universitas Pamulang
  • Muhamad Rahmat Fadila Universitas Pamulang

Keywords:

Coronary Heart Disease, Classification, Extreme Learning Machine

Abstract

Coronary Heart Disease (CHD) is a leading cardiovascular disease and one of the primary causes of death worldwide. Early and accurate classification of CHD can aid in effective prevention and appropriate treatment. This study aims to develop a CHD classification model using the Extreme Learning Machine (ELM) method. The research methodology includes gathering CHD data from the Cleveland Heart Disease Dataset, data preprocessing, dividing data into training and testing sets, and implementing the ELM algorithm for classification. Additionally, a literature review was conducted to identify related studies on heart disease classification using machine learning methods. The results indicate that the ELM model can classify CHD effectively and efficiently compared to other methods such as Support Vector Machine (SVM) and Artificial Neural Network (ANN). Therefore, ELM presents a promising alternative for early CHD diagnosis.

References

He, W., Xie, Y., Lu, H., Wang, M., & Chen, H. (2020). A new method for coronary artery disease prediction using improved extreme learning machine with salp swarm algorithm. Computers in Biology and Medicine, 122, 104723. https://doi.org/10.1016/j.compbiomed.2021.104723

Anisa Maulida, Arisky Rahmatulloh, Irwan Ahussalim, Robby Alvian, & Perani Rosyani. (2023). Analisis Metode Forward Chaining pada Sistem Pakar: Systematic Literature Review. Vol 1 No 4 Juni 2023.

Bakhshi, H., Ambale-Venkatesh, B., Yang, X., Ostovaneh, M. R., Wu, C. O., Budoff, M., Bahrami, H., Wong, N. D., Bluemke, D. A., Lima, J. A. C. (2017). Progression of coronary artery calcium and risk of heart failure and left ventricular dysfunction. Journal of the American Heart Association, 6(5), e005253. https://doi.org/10.1161/JAHA.116.005253

Koloi, A., Loukas, V. S., Hourican, C., Sakellarios, A. I., Quax, R., Mishra, P. P., Lehtimäki, T., Raitakari, O. T., Papaloukas, C., Bosch, J. A., März, W., Fotiadis, D. I. (2024). Early-stage coronary artery disease prediction using clinical and laboratory data: A machine learning approach. European

Heart Journal - Digital Health, 5(5), 542-550. https://doi.org/10.1093/ehjdh/ztad0937

Budoff, M. J., Lopez, V. A., Nasir, K., Blumenthal, R. S., Detrano, R. C., Kronmal, R., Bild, D., Guerci, A., Liu, K., Shea, S., Szlko, M., Post, W., Lima, J. A., Bertoni, A., Wong, N. D. (2011). Coronary artery calcium progression and coronary heart disease risk: The multiethnic study of atherosclerosis. Journal of the American College of Cardiology, 57(13), 14341440. https://doi.org/10.1016/j.jacc.2010.12.015

Ahmad, G. N., Shafiullah, Fatima, H., Abbas, M., Rahman, O., Imdadullah, Alqahtani, M. S. (2022). Efficient heart disease prediction using machine learning techniques: An approach to feature extraction and classification. Applied Sciences, 12(15), 7449. https://doi.org/10.3390/app12157449

Uddin, S., Khan, A., Hossain, M. E., & Moni, M. A. (2019). Comparing different supervised machine learning algorithms for disease prediction. BMC Medical Informatics and Decision Making, 19, 281. https://doi.org/10.1186/s12911-019-1004-8

Perani Rosyani, Gugum Gumelar, Ray Diphan, Willa Agustin, & Mega Christina. (2023). Literatur Riview Sistem Pakar Mengindentifikasi Penyakit Jantung dan Paru-paru Menggunakan Metode Forward Chaining. Jurnal Ilmu Komputer, Teknik, dan Multimedia, Vol 1-No 1.

https://doi.org/10.9999/1gy34081

Jefri Junifer Pangaribuan, Cathlin Tedja, & Sentosa Wibowo. (2019). Perbandingan Metode Algoritma C4.5 dan Extreme Learning Machine Untuk Mendiagnosis Penyakit Jantung Koroner. Informatics Engineering Research and Technology, Vol 1-No 1 Agus 2019.

Choi, S. I., Kim, J. S., Kim, J. K., & Park, J. H. (2021). Machine learning-based prediction model for coronary artery disease using clinical data and coronary artery calcium scores. PLoS One, 16(9), e0257591. https://doi.org/10.1371/journal.pone.0257591

Haq, A. U., Li, J. P., Memon, M. H., Nazir, S., Sun, S., & Ru Yu, D. (2018). A hybrid intelligent system framework for the prediction of heart disease using machine learning algorithms. Mobile Information Systems, 2018, 3860146. https://doi.org/10.1155/2018/3860146

Alam, T. M., & Mehmood, M. (2022). Explainable AI in healthcare for early diagnosis of cardiovascular diseases using ensemble learning. Scientific Reports, 12(1), 1-12. https://doi.org/10.1038/s41598-022-13929-8

Zhu, H., & Li, Y. (2020). Predicting coronary heart disease with machine learning based on electronic health records. Journal of Medical Systems, 44, 70.https://doi.org/10.1007/s10916-020-1535-y

Additional Files

Published

15-11-2024

How to Cite

Marwan Kosasih, Sahrul Ramadhani, Arni Susanti Ndruru, Reihan Renaldi, & Muhamad Rahmat Fadila. (2024). Literatur Review: Klasifikasi Penyakit Jantung Koroner Menggunakan Extreme Learning Machine. OKTAL : Jurnal Ilmu Komputer Dan Sains, 3(09), 2356–2361. Retrieved from https://journal.mediapublikasi.id/index.php/oktal/article/view/4682