SYNOPSIS

In this session, we first give an overview on the impact of data science on health care delivery and research. We then give some examples on how AI and machine learning was used to create high-value blood tests based on genomics and proteomics data. Finally, from research to clinical decision making, we introduce the various opportunities of using Natural Language Processing and Large Language Models to interpret clinical documents.

At the end of this session, participants will:

1. Understand what is data science;
2. Learn what are the core components of data science;
3. Understand what are the opportunities when data science meets advances in biotechnologies;
4. Learn what are the key challenges in maximizing the value of data science in healthcare and research;
5. Identify examples when machine learning is applied to genomics research;
6. Identify how Natural Language Processing and Large Language Models can be used in clinical settings.