Day 3: AI & ML techniques in biomedical research

Learning objectives

• Explain the principles, capabilities, and limitations of key AI and machine learning (ML) techniques in biomedical research.
• Evaluate and select appropriate AI/ML approaches for specific biomedical and precision health applications.

Lectures

[09:00-10:30] Lecture 1: Network medicine tools for data-driven health

Speaker: Mika Gustafsson

The network models (e.g., deep neural network) and their applications in biomedical research.

[10:30-10:45] Break

[10:45-12:00] Lecture 2: Generative AI for Omics analysis

Speaker: Wen Zhong

Introduction of machine learning methods, and generative AI (e.g., Transformer) and their application in biomedical research.

Workshops

[13:00-14:00] Workshop 1: Classical ML methods

Workshop instructor: Xingyue Wang

Common modeling tasks, such as regression, binary classification, and multi-class classification, and the basic pipeline for training and evaluating models.

[14:00-16:00] Workshop 2: Generative AI models for omics analysis

Workshop instructor: Xiangyu Qiao

The application of pre-trained generative AI models for the classification of cell types and the identification of cell markers.