1:30-2:00pm

Establishing datasets and standards

1. What are the available curated datasets that can be used for establishing AI/ML standards in biomarker discovery
2. What minimal essential standards need to be put into place for application of AI/ML in the EDRN ecosystem (who defines “ground truth”)
3. Cross sectional versus longitudinal studies
4. Segmentation standards and role of pathologists

2:00-2:30pm

Applications of AI/ML in Precancer Lesions and Biomarker Discovery (Cross pollination with Spatial omics, radiomics, and cell free DNA groups)

1. What role could AI/ML play in in silico biomarker discovery from spatial cell analysis of precancer lesions
2. How can AI/ML approaches help us in understanding cellular neighborhoods and cell communication in 3D (most spatial analyses approaches these days are in 2D, but 3D approaches were discussed extensively at AACR)
3. How can AI/ML approaches on tissues be integrated with blood-based biomarker work including cell free DNA and other marker modalities.
4. How can AI/ML on tissues be integrated with imaging datasets and radiomics studies
5. “Grand unification” (tissue, imaging, blood, others)

2:30-3:00pm

Open Discussion and Summary

1: Should EDRN constitute an AI/ML working group for biomarker discovery and integration?

2: What are the best avenues for data storage and standards for data access?