Integrate complex network with machine learning algorithms to improve cancer detection

molahoseini ardakani, Mohammadreza; amrolahi, sadra

[Home ] [Archive]

[ فارسی ]

Main Menu

Home

Journal Information

Articles archive

For Authors

For Reviewers

Registration

Contact us

Site Facilities

Search in website

Receive site information

Volume 4, Issue 7 (5-2025)

3 2025, 4(7): 18-27

Back to browse issues page

Integrate complex network with machine learning algorithms to improve cancer detection

Mohammadreza Molahoseini ardakani

, Sadra Amrolahi

Islamic azad university

Abstract: (67 Views)

Detecting and distinguishing brain tumors and inflammatory lesions in MRI images is crucial for timely and effective treatment. In this study, we extracted features of brain tumors and inflammatory lesions from MRI images of the Kaggel dataset by using a complex network with simplified network architecture and integrated it with a machine learning algorithm to detect brain cancer. Machine learning algorithms including Logistic Regression, Random Forest, KNN, Naive Bayes and SVM were used to classify the images, and their performance was evaluated using accuracy, precision, F1-score, recall, and ROC curve parameters.
Our results show that all classification algorithms achieved high accuracy rates, with the highest being 90.26%. By using a complex network with simplified network architecture to extract image features, we were able to improve the accuracy of distinguishing between inflammatory lesions and brain tumors. This research has significant implications for patient screening, as rapid and accurate classification of brain tumors and inflammatory lesions can facilitate timely treatment.
In conclusion, our study demonstrates the potential of using machine learning algorithms in combination with MRI image analysis to distinguish between inflammatory lesions and brain tumors accurately. Our results provide a promising basis for further research, and the system can be directly applied in practice.

Keywords: MRI images, Complex network, Machine learning algorithm, Inflammatory lesion, Mass cancer

Full-Text [PDF 784 kb] (43 Downloads)

Type of Study: Applicable | Subject: Special
Received: 2023/04/20 | Accepted: 2025/02/8 | Published: 2025/06/12

References

1. McFaline-Figueroa JR, Lee EQ. 2018. Brain tumors. Am J Med. 131 (8):874–882. doi:10.1016/j.amjmed.2017.12.039.

2. Jeong H-K, Ji K, Min K, Joe E-H. 2013. Brain inflammation and microglia: facts and misconceptions. Exp Neurobiol. 22(2):59. doi:10.5607/en.2013.22.2.59.

3. Estrada E. 2015. Introduction to Complex Networks: Structure and Dynamics. In Banasiak, J., Mokhtar-Kharroubi, M, editor(s). Evolutionary Equations with Applications in Natural Sciences. Lecture Notes in Mathematics, vol. 2126. Springer, Cham.

4. Mata A. S. D. 2020. Complex networks: a mini-review. Brazilian Journal of Physics. 50(5):658–672. https://doi.org/10.1007/s13538-020-00772-9

5. Khan HA, Jue W, Mushtaq M, Mushtaq MU. 2020. Brain tumor classification in MRI image using convolutional neural network. Math Bio Sci Eng. 17 (5):6203. doi:10.3934/mbe.2020328.

6. Vargo M. 2011. Brain tumor rehabilitation. Am J Phys Med Rehabil. 90(5): S50–S62. doi:10.1097/PHM.0b013e31820be31f.

7. Barbieri AL, De Arruda G, Rodrigues FA, Bruno OM, da Fontoura Costa L. 2011. An entropy-based approach to automatic image segmentation of satellite images. Phys Stat Mech Its Appl. 390(3):512–518. doi:10.1016/j. physa.2010.10.015.

8. Da Fontoura Costa, L. 2004. Complex networks, simple vision. arXiv e-prints, pp.cond–mat. https://doi.org/10.48550/arXiv.cond-mat/0403346

9. Backes AR, Casanova D, Bruno OM. 2010. A complex network-based approach for texture analysis. In: Iberoamerican Congress on Pattern Recognition. Springer; p. 354–361.

10. E. Gohariyan, M. Esmaeilpour, and M. M. Shirmohammadi, "The Combination of Mammography and MRI for Diagnosing Breast Cancer Using Fuzzy NN and SVM," Int. J. Interact. Multim. Artif. Intell., vol. 4, no. 5, pp. 20–24, Sep. 2017.

Add your comments about this article

Mendeley

Zotero

RefWorks

molahoseini ardakani M, amrolahi S. Integrate complex network with machine learning algorithms to improve cancer detection. 3 2025; 4 (7) :18-27
URL: http://jiis.iauh.ac.ir/article-1-30-en.html

Rights and permissions
	This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Volume 4, Issue 7 (5-2025)

Back to browse issues page

Persian site map - English site map - Created in 0.05 seconds with 37 queries by YEKTAWEB 4714