Implementation of Neural Network Algorithm (RNN) for Lung Disease Classification

DOI

10.2991/978-94-6463-998-8_17How to use a DOI?

Keywords

Lung Diseases; Classification; Recurrent Neural Network; X-ray Images; Medical Diagnosis

Abstract

This research examines the classification of lung diseases using the Recurrent Neural Network algorithm, based on medical images, specifically X-ray images. The method aims to improve the accuracy of lung disease diagnosis by leveraging the capabilities of Recurrent Neural Networks in recognizing complex patterns in sequential data. RNNs are particularly suited for this task due to their ability to process sequences of data, making them effective in analyzing time-dependent or ordered information. In this study, an RNN model has been developed and evaluated using a dataset of lung X-ray images sourced from reputable medical databases. The dataset encompasses various lung conditions, including pneumonia, tuberculosis, and lung cancer, allowing for comprehensive model training. The results show that the RNN model achieves an accuracy of 62.9 percent, indicating its potential in supporting automated medical diagnostic processes. While this accuracy is promising, it also highlights the need for further development and fine-tuning of the model to enhance performance. By improving the accuracy of automated diagnoses, this research contributes significantly to the advancement of decision support systems for clinical practice in the medical field, ultimately aiding healthcare professionals in delivering timely and accurate diagnoses for lung diseases.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Tengku Daffa Syauky Ghifari
AU  - Garell Dane Audric Tanoto
AU  - Ivan Putra Pandawa
AU  - Ferdian Liyanto
AU  - Agung Prabowo
PY  - 2026
DA  - 2026/03/05
TI  - Implementation of Neural Network Algorithm (RNN) for Lung Disease Classification
BT  - Proceedings of the 1st International Conference of Technology, Innovation, Design & Enterprise (ICTIDE 2025)
PB  - Atlantis Press
SP  - 128
EP  - 138
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-998-8_17
DO  - 10.2991/978-94-6463-998-8_17
ID  - Ghifari2026
ER  -