Artificial Intelligence in Hepatitis Diagnosis, Treatment and Drug Discovery: Current Advances, Challenges and Future Perspectives

Abstract

AI has proven to be revolutionary in terms of its application in healthcare for the diagnosis, treatment, and management of various infectious diseases such as hepatitis. Hepatitis is a condition that is associated with infection from several hepatitis viruses, namely, hepatitis A, B, C, D, and E, which affects many millions of individuals and results in the death of individuals due to liver complications such as chronic liver disease, cirrhosis, and hepatocellular carcinoma. The advancement of AI has seen an improvement in the way diseases can be managed, specifically in machine learning (ML), deep learning (DL), natural language processing (NLP), and computer vision. AI has shown great potential in enhancing hepatitis care, through the use of AI algorithms that can analyze clinical data, laboratory tests, images, and genomics data for better diagnosis, predicting the progression of the disease, tailoring treatment strategies, and facilitating the discovery of drugs.AI is also involved in the detection of novel antiviral agents, vaccines, and biomarkers using multi-omics and massive amounts of biomedical data. In spite of all these advantages, there are still various challenges such as data privacy, transparent algorithms, ethical considerations, approval from regulators, and the requirement of quality data sets. This review aims to highlight recent trends in AI utilization in hepatitis diagnostics, treatment, precision medicine, and drug discovery, and future opportunities related to these aspects.