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Metaheuristic Optimization Review

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Online: 3066-280X
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Semi-annual (January, June)

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Open access journal. All articles are freely available online with no APC.

Metaheuristic Optimization Review
Full Length Article

Volume 3Issue 1PP: 01-11 • 2025

Optimization Algorithms for Deep Learning Prediction of Liver cirrhosis: A Survey

Aya Ebrahim 1* ,
Asmaa H. Rabie 2 ,
El-Sayed M. El-Kenawy 3 ,
Hossam El-Din Moustafa 4
1Department of Applied Health Sciences, Higher Technological Institute of Applied Health Sciences, Mansoura, Egypt
2Department of Computers Engineering and Control Systems, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt
3Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt
4Professor at the Department of Electronics and Communications Engineering, Faculty of Engineering, Mansoura University, Egypt
* Corresponding Author.
Received: October 16, 2024 Revised: December 01, 2024 Accepted: December 13, 2024

Abstract

Today, new Artificial Intelligence (AI) techniques are utilized to help doctors forecast the occurrence of diseases because of the necessity of sustaining public health and early disease diagnosis. One significant kind of liver damage is liver cirrhosis, which typically results from long-term liver damage brought on by a variety of liver conditions and diseases, including hepatitis, persistent alcoholism, or heredity. We created this review to provide an overview of liver cirrhosis since it is essential to identify it early and prevent the damage from spreading throughout the liver tissues. In order to identify liver cirrhosis from biomedical markers rather than images, this study has recently conducted nine studies overlaying it with various artificial intelligence deep learning techniques. Our suggested approach used various Machine Learning (ML) models to predict the signs of cirrhosis in conjunction with other illnesses. Because this condition is so important, it is important to summarize these studies based on the methodology and findings of detection accuracy and precision.

Keywords

Liver Cirrhosis artificial intelligence deep learning Optimization algorithms.

References

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[16] Fedesoriano. (Aug. 2021). Cirrhosis Prediction Dataset. [Online]. Available: https://www.kaggle.com/fedesoriano/cirrhosis-prediction-dataset

 

 

 

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Ebrahim, Aya, Rabie, Asmaa H., El-Kenawy, El-Sayed M., Moustafa, Hossam El-Din. "Optimization Algorithms for Deep Learning Prediction of Liver cirrhosis: A Survey." Metaheuristic Optimization Review, vol. Volume 3, no. Issue 1, 2025, pp. 01-11. DOI: https://doi.org/10.54216/MOR.030101
Ebrahim, A., Rabie, A., El-Kenawy, E., Moustafa, H. (2025). Optimization Algorithms for Deep Learning Prediction of Liver cirrhosis: A Survey. Metaheuristic Optimization Review, Volume 3(Issue 1), 01-11. DOI: https://doi.org/10.54216/MOR.030101
Ebrahim, Aya, Rabie, Asmaa H., El-Kenawy, El-Sayed M., Moustafa, Hossam El-Din. "Optimization Algorithms for Deep Learning Prediction of Liver cirrhosis: A Survey." Metaheuristic Optimization Review Volume 3, no. Issue 1 (2025): 01-11. DOI: https://doi.org/10.54216/MOR.030101
Ebrahim, A., Rabie, A., El-Kenawy, E., Moustafa, H. (2025) 'Optimization Algorithms for Deep Learning Prediction of Liver cirrhosis: A Survey', Metaheuristic Optimization Review, Volume 3(Issue 1), pp. 01-11. DOI: https://doi.org/10.54216/MOR.030101
Ebrahim A, Rabie A, El-Kenawy E, Moustafa H. Optimization Algorithms for Deep Learning Prediction of Liver cirrhosis: A Survey. Metaheuristic Optimization Review. 2025;Volume 3(Issue 1):01-11. DOI: https://doi.org/10.54216/MOR.030101
A. Ebrahim, A. Rabie, E. El-Kenawy, H. Moustafa, "Optimization Algorithms for Deep Learning Prediction of Liver cirrhosis: A Survey," Metaheuristic Optimization Review, vol. Volume 3, no. Issue 1, pp. 01-11, 2025. DOI: https://doi.org/10.54216/MOR.030101
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