The Liver Meeting 2021-Part I - Basics of Navigating Artificial Intelligence in Liver Research

Part I - Basics of Navigating Artificial Intelligence in Liver Research

Video Transcription

Video Summary

The video transcript summarizes a seminar organized by the Clinical Research Committee of the American Association for the Study of Liver Disease on using artificial intelligence (AI) in liver disease research. It covers topics like datasets, radiology, pathology, and multi-omics, discussing basic AI concepts and advanced applications such as using CNN and RNN. The importance of enriching data sources for predictive algorithms to address biases and limitations is highlighted. The potential of AI in improving clinical decision support and risk stratification in hepatology is presented, along with the emphasis on addressing bias, transparency, and security in AI applications. Moreover, the discussion focuses on multi-omics data integration, challenges in single omics data analysis, collaboration between clinicians and analysts, data validation, addressing bias, and standardizing data acquisition methods. The need for multidisciplinary collaboration and continuous learning to enhance the accuracy and applicability of AI algorithms in clinical practice is also emphasized. Overall, the video provides insights into the advancements and potential of AI in liver disease research.

Keywords

Artificial intelligence

Liver disease research

Datasets

Radiology

Pathology

Multi-omics

CNN

RNN

Predictive algorithms

Clinical decision support

Risk stratification

Data integration