Classification of Heart Disease using Artificial Neural Network

Heart disease refers to any unavoidable condition that affects a person's heart. With so much electronic health data available nowadays, computer machines have entered the area to aid in diagnosis using machine learning (ML) methodologies. This study focuses on classification of heart disease t...

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Bibliographic Details
Published in:Journal of physics. Conference series 2021-08, Vol.1997 (1), p.12022
Main Authors: Tick, Voon Khai, Meeng, Ng Yung, Mohammad, Nur Farahiyah, Harun, Nor Hazlyna, Alquran, Hiam, Mohsin, Mohamad Farhan Mohamad
Format: Article
Language:English
Subjects:
Artificial neural networks
Back propagation networks
Cardiovascular disease
Classification
Heart
Heart diseases
Learning theory
Machine learning
Multilayers
Neural networks
Physics
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Summary:Heart disease refers to any unavoidable condition that affects a person's heart. With so much electronic health data available nowadays, computer machines have entered the area to aid in diagnosis using machine learning (ML) methodologies. This study focuses on classification of heart disease that includes or does not include heart attacks and employs an artificial neural network (ANN) namely Multi-layered Perceptron (MLP) trained by Back-propagation (BP) to classify the data. By going through layers of functions, ANN can identify the trends of the data then form a model. This study uses sigmoid activation functions and runs in 1000 numbers of epochs. Different values of learning rate and neuron numbers were tested and yielded with the best result. The findings recorded high accuracy of 80.66% with 0.25 learning rate and 25 neurons. It is learned that ANN can be used for classifying heart disease cases.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1997/1/012022