Artificial Intelligence in Hepatology- Ready for the Primetime.
Rakesh Kalapala1, Hardik Rughwani1, D Nageshwar Reddy2
1Department of Gastroenterology, Asian Institute of Gastroenterology and AIG Hospitals, Hyderabad, India.
Journal of Clinical and Experimental Hepatology
|January 17, 2023
Summary
Artificial Intelligence (AI) shows promise in hepatology for improving patient management and treatment outcomes. Further research is needed to validate AI tools for diagnosing and managing liver diseases.
Area of Science:
- Hepatology
- Artificial Intelligence
- Medical Informatics
Background:
- Artificial Intelligence (AI) is evolving to support human intelligence through algorithmic design.
- AI applications in hepatology are emerging, offering potential for improved patient management and treatment outcomes.
- Current clinical use of AI in hepatology is limited, with tools like machine learning and deep learning under development.
Purpose of the Study:
- To review various applications of AI in hepatology.
- To discuss the challenges and future implications of AI in liver disease management.
- To summarize the current state of AI models and algorithms in hepatology research.
Main Methods:
- Review of existing literature on AI applications in hepatology.
- Analysis of AI models utilizing clinical, laboratory, endoscopic, and imaging data.
- Examination of AI's role in diagnosing liver diseases and mass lesions.
Main Results:
- AI tools are being developed to aid in the diagnosis and management of liver diseases.
- AI has the potential to reduce human error and enhance treatment protocols in hepatology.
- Various AI models are under study, employing diverse datasets for liver disease assessment.
Conclusions:
- AI demonstrates significant promise for advancing hepatology practice.
- Further research and clinical validation are essential for the widespread adoption of AI in hepatology.
- AI integration may lead to more precise and effective management of liver conditions.
Keywords:
ACLF, acute on chronic liver failureAI, artificial intelligenceALD, alcoholic liver diseaseALT, alanine transaminaseANN, artificial neural networkAST, aspartate aminotransferaseAUD, alcohol use disorderCHB, chronic hepatitis BCHC, chronic hepatitis CCLD, chronic liver diseaseCNN, convolutional neural networkDL, deep learningFIB-4, fibrosis-4 scoreGGTP, gamma glutamyl transferaseHCC, hepatocellular carcinomaHDL, high density lipoproteinML, machine learningMLR, multi-nomial logistic regressionsNAFLDNAFLD, non-alcoholic fatty liver diseaseNASH, non-alcoholic steatohepatitisNLP, natural language processingRF, random forestRTE, real-time tissue elastographySOLs, space-occupying lesionsSVM, support vector machineartificial intelligencedeep learninghepatologymachine learning
