A Comprehensive Analysis of Cirrhosis Progression through Clinical Data
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Abstract
Cirrhosis is a progressive liver disease characterized by liver fibrosis and scarring, which can eventually lead to liver failure. It is primarily caused by chronic alcohol con- sumption, viral hepatitis, and non-alcoholic fatty liver disease (NAFLD). Early detection and diagnosis are crucial for pre- venting the progression of the disease. Recent advancements in machine learning and deep learning techniques have shown great promise in enhancing the diagnostic accuracy of cirrhosis through non-invasive methods, such as medical imaging analysis and biomarker prediction. These techniques aid in early-stage detection, ultimately improving patient prognosis and manage- ment. This paper explores various methods of cirrhosis detection, with a focus on artificial intelligence applications that automate diagnosis, enabling clinicians to make better-informed decisions.