AI-Driven Tumor Microenvironment Analysis

The tumor microenvironment (TME) plays a pivotal role in tumor progression, metastasis, and response to treatment. Understanding the interactions between tumor cells, immune cells, blood vessels, and extracellular matrix components is crucial for developing effective cancer therapies. However, the complexity of the TME has made it difficult to study using traditional methods.
AI has emerged as a powerful tool to analyze high-dimensional data from the TME, such as imaging data, genomic information, and molecular profiles. This workshop will focus on AI techniques like machine learning and deep learning to better understand TME dynamics, predict patient outcomes, and optimize therapeutic strategies. Participants will also gain hands-on experience in using AI to analyze multi-modal data from the TME, with a particular emphasis on improving personalized cancer treatment.

This workshop aims to explore the use of Artificial Intelligence (AI) to analyze the tumor microenvironment (TME), focusing on how AI can help in understanding tumor biology, predicting treatment responses, and enhancing cancer therapies. Participants will learn how AI models can integrate complex data from the TME to improve cancer diagnosis, prognosis, and personalized treatment plans.

• Understand the composition and dynamics of the tumor microenvironment (TME).
• Learn how AI can be used to analyze complex TME data for tumor characterization.
• Gain hands-on experience in applying machine learning and deep learning to TME analysis.
• Explore how AI models can predict treatment responses and patient outcomes based on TME data.
• Analyze real-world case studies to understand how AI-driven TME analysis can enhance cancer therapy and prognosis.