Chapter 16 - Outlook of future landscape of artificial intelligence in health care of liver disease and challenges

Abstract

Artificial intelligence (AI) is growing in importance in hepatology. Various sources of data from electric health records, radiology, and pathology have been used to develop AI models for nonalcoholic fatty liver disease, viral hepatitis, cirrhosis, acute liver failure, liver transplantation, hepatocellular carcinoma, drug-induced liver injury, and precision medicine. AI will soon be integrated in the clinical workflow to manage liver disease, although several issues need to be considered. AI will facilitate interdisciplinary care and collaboration with physicians, but it will not replace them. Data are crucial in the development of AI algorithms, whereas the collection and standardization of medical data from various sources are important to develop AI models, so data disparity and security should be carefully managed. The deployment and efficacy of AI models should be evaluated in clinical scenarios. Several novel fields of AI research involve training models using multimodal data and multiomics data. Advances in natural language processing help to explore unstructured electric health records. Digital epidemiology, digital twins, and federated learning are other trends. Telemedicine and self-monitoring using multiple wearable devices facilitate a useful paradigm of health care. The era of AI will transform the health care of liver disease.