A Comprehensive Review of Liver Diseases: Classification, Diagnosis, Risk Factors, and Emerging Artificial Intelligence-Based Prediction Approaches

Authors

  • Anshita Prabhakar, Ashish Kumar Tiwari

Keywords:

Deep Learning, Machine Learning, Artificial Intelligence, Liver Failure, Hepatitis, Liver Diseases

Abstract

Diseases of the liver present a considerable challenge for world health due to their increasing incidence, complicated mechanisms, and great impact on mortality. The liver has several important functions such as metabolism, detoxification, secretion of bile, and regulation of biochemical processes and any abnormalities, both functional and structural, can result in serious health consequences. The present review article is a detailed review of the liver diseases including fatty liver disease, hepatitis, alcoholic liver diseases, fibroses, cirrhosis, autoimmune disorders, liver failure, and hepatocellular carcinoma. The article describes the causes of liver diseases, their symptoms, process of diagnosis, and underlying mechanisms of diseases development. Different diagnostic methods such as biochemical tests, imaging methods, and biopsy as well as problems connected with the diagnosis of the early stages of the diseases are examined. Advanced developments in machine learning and deep learning in liver disease prediction, classification, and decision support system also discussed. The issue of obtaining and working with complicated medical datasets as well as a high precision during diagnostics is also discussed. Problems of obtaining and analysing the data as well as the staying in line with privacy regulations and the medical community acceptance are also analysed.

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How to Cite

Anshita Prabhakar, Ashish Kumar Tiwari. (2026). A Comprehensive Review of Liver Diseases: Classification, Diagnosis, Risk Factors, and Emerging Artificial Intelligence-Based Prediction Approaches. International Journal of Research & Technology, 14(2), 1965–1976. Retrieved from https://ijrt.org/j/article/view/1634

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Original Research Articles

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