Articles | Open Access |

REVOLUTIONIZING LIVER DISEASE DIAGNOSIS: THE MACHINE LEARNING FRONTIER

Arshad Khan , City University of Science and Information Technology, Peshawar, Pakistan

Abstract

The diagnosis of liver diseases presents a formidable challenge in healthcare, given their diverse etiologies and complex clinical presentations. Leveraging the power of machine learning, this study explores a promising frontier in liver disease diagnosis. We investigate the application of machine learning algorithms to a variety of clinical and laboratory data, aiming to enhance the accuracy and efficiency of liver disease diagnosis. By analyzing a comprehensive dataset and utilizing advanced computational techniques, we uncover valuable patterns, markers, and predictive models that can significantly aid healthcare practitioners in timely and precise liver disease identification and management.

Keywords

Machine Learning, Liver Disease Diagnosis, Healthcare

References

N. Arbain and B. Y. P. Balakrishnan, “A Comparison of Data Mining Algorithms for Liver Disease Prediction on Imbalanced Data,” Int. J. Data Sci. Adv. Anal., 2019.

N. Nahar and F. Ara, “Liver Disease Prediction by Using Different Decision Tree Techniques,” Int. J. Data Min. Knowl. Manag. Process, vol. 8, no. 2, pp. 01–09, 2018.

U. Student, U. Sriwijaya, U. Sriwijaya, and U. Sriwijaya, “Issn 2598 0580,” vol. 3, no. 1, pp. 51–63, 2019.

J. E. Hay, “Acute liver failure,” Curr. Treat. Options Gastroenterol., vol. 7, no. 6, pp. 459–468, 2004.

R. A. Hauser, T. A. Zesiewicz, A. S. Rosemurgy, C. Martinez, and C. W. Olanow, “Manganese intoxication and chronic liver failure,” Ann. Neurol., vol. 36, no. 6, pp. 871–875, 1994.

S.Dhamodharan, “Liver Disease Prediction Using Bayesian Classfication,” 4th Natl. Conf. Adv. Comput. Appl. Technol., no. May, pp. 1–3, 2014.

M. S. D. Dr. S. Vijayarani1, “Liver Disease Prediction using SVM and NaïveBayes Algorithms,” Int. J. Sci. Eng. Technol. Res., vol. 4, no. 4, pp. 816–820, 2015.

K. Morik, “Medicine: Applications of Machine Learning,” Encycl. Mach. Learn. Data Min., pp. 809–817, 2017.

Gunawardana and G. Shani, “A survey of accuracy evaluation metrics of recommendation tasks,” J. Mach. Learn. Res., vol. 10, pp. 2935–2962, 2009.

Kaushik, A. Chauhan, D. Mittal, and S. Gupta, “COCOMO Estimates Using Neural Networks,” Int. J. Intell. Syst. Appl., vol. 4, no. 9, pp. 22–28, 2012.

Article Statistics

Downloads

Download data is not yet available.

Copyright License

Download Citations

How to Cite

REVOLUTIONIZING LIVER DISEASE DIAGNOSIS: THE MACHINE LEARNING FRONTIER. (2022). International Journal of Data Science and Machine Learning, 2(02), 01-04. https://www.academicpublishers.org/journals/index.php/ijdsml/article/view/49