Literature Review: Klasifikasi Citra Medis Penyakit Pneumonia dengan Convolutional Neural Network

Noufal Maulana; Muhammad Fauzan Rusby Kholiq; Muhammad Dabit H. A.; Geraldo Sabila F.

Authors

Noufal Maulana Universitas Pamulang
Muhammad Fauzan Rusby Kholiq Universitas Pamulang
Muhammad Dabit H. A. Universitas Pamulang
Geraldo Sabila F. Universitas Pamulang

Keywords:

Pneumonia, Convolutional Neural Network, X-Ray Image, Classification, Automatic Diagnosis

Abstract

Pneumonia is a dangerous respiratory infection with a fairly high mortality rate, especially in countries with limited medical resources. Examination of chest X-ray images is usually the main method for diagnosing this disease, but the process can be time consuming and requires special expertise. In this study, the Convolutional Neural Network (CNN) method was applied to help classify chest X-ray images into "pneumonia" and "normal" categories. By using CNN, this model is able to recognize complex visual patterns in images and produce predictions with a high level of accuracy. The test results show that the CNN model can be relied upon to assist in the automatic diagnosis of pneumonia, providing opportunities for application on a wider scale.

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