Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images

Çiğdem Saraç; Seda Arıkan Arıbal; Yiğit Ali Üncü

doi:10.29233/sdufeffd.1694369

Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images

Abstract

Brain cancer, resulting from abnormal tumor growth in brain tissue, requires accurate and timely diagnosis. Although MRI plays a crucial role, manual interpretation is prone to errors and delays. To address this, we propose a hybrid system combining deep learning (VGG16, ResNet50, DenseNet201) with reinforcement learning (Q-learning) for brain tumor classification. Using three distinct MRI datasets within MATLAB, the models achieved high classification accuracies: 97.45% (VGG16), 96.06% (ResNet50), and 96.93% (DenseNet201). The integration of reinforcement learning improved decision-making and interpretability. Additionally, a user-friendly interface was developed to support clinical decision-making. This study demonstrates that combining deep learning with reinforcement learning enhances model adaptability, offering a more reliable and effective diagnostic approach.

Keywords

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Details

Primary Language

English

Subjects

Bioinformatics and Computational Biology (Other)

Journal Section

Research Article

Authors

Çiğdem Saraç ^*
0000-0002-3538-6551
Türkiye

Seda Arıkan Arıbal
0009-0009-9067-0502
Türkiye

Yiğit Ali Üncü
0000-0001-7398-9540
Türkiye

Publication Date

November 26, 2025

Submission Date

May 7, 2025

Acceptance Date

November 14, 2025

Published in Issue

Year 2025 Volume: 20 Number: 2

DOI

https://doi.org/10.29233/sdufeffd.1694369

IZ

https://izlik.org/JA76CZ36PF

Cite

RIS / Bibtex

APA

Saraç, Ç., Arıkan Arıbal, S., & Üncü, Y. A. (2025). Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images. Süleyman Demirel University Faculty of Arts and Science Journal of Science, 20(2), 206-221. https://doi.org/10.29233/sdufeffd.1694369

AMA

1.Saraç Ç, Arıkan Arıbal S, Üncü YA. Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images. Süleyman Demirel University Faculty of Arts and Science Journal of Science. 2025;20(2):206-221. doi:10.29233/sdufeffd.1694369

Chicago

Saraç, Çiğdem, Seda Arıkan Arıbal, and Yiğit Ali Üncü. 2025. “Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images”. Süleyman Demirel University Faculty of Arts and Science Journal of Science 20 (2): 206-21. https://doi.org/10.29233/sdufeffd.1694369.

EndNote

Saraç Ç, Arıkan Arıbal S, Üncü YA (November 1, 2025) Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images. Süleyman Demirel University Faculty of Arts and Science Journal of Science 20 2 206–221.

IEEE

[1]Ç. Saraç, S. Arıkan Arıbal, and Y. A. Üncü, “Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images”, Süleyman Demirel University Faculty of Arts and Science Journal of Science, vol. 20, no. 2, pp. 206–221, Nov. 2025, doi: 10.29233/sdufeffd.1694369.

ISNAD

Saraç, Çiğdem - Arıkan Arıbal, Seda - Üncü, Yiğit Ali. “Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images”. Süleyman Demirel University Faculty of Arts and Science Journal of Science 20/2 (November 1, 2025): 206-221. https://doi.org/10.29233/sdufeffd.1694369.

JAMA

1.Saraç Ç, Arıkan Arıbal S, Üncü YA. Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images. Süleyman Demirel University Faculty of Arts and Science Journal of Science. 2025;20:206–221.

MLA

Saraç, Çiğdem, et al. “Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images”. Süleyman Demirel University Faculty of Arts and Science Journal of Science, vol. 20, no. 2, Nov. 2025, pp. 206-21, doi:10.29233/sdufeffd.1694369.

Vancouver

1.Çiğdem Saraç, Seda Arıkan Arıbal, Yiğit Ali Üncü. Hybrid Deep Learning and Reinforcement Learning Approach for Brain Tumor Classification from MRI Images. Süleyman Demirel University Faculty of Arts and Science Journal of Science. 2025 Nov. 1;20(2):206-21. doi:10.29233/sdufeffd.1694369