The Role of Pathology AI in Translational Cancer Research and Education

Learn how digital pathology is rapidly transforming cancer research through AI-driven analysis of whole slide images.

Join Stony Brook University’s Dr. Joel Saltz as he discusses:

• the role of pathology AI in the creation of pathology imaging biomarkers, including tumor infiltrating lymphocytes and prediction of molecular cancer sub-classification and molecular risk of recurrence assessments.
• methods he and his group are developing to improve interpretability of AI models.
• new methods he and his group have developed for generating highly realistic, multi-scale, synthetic pathology images using novel conditional latent diffusion methods that they have also developed. You can use these methods for a variety of downstream tasks, including data augmentation for supervised and unsupervised model training, segmentation, as well as for training and education.

The CBIIT Data Science Seminar Series is dedicating its 2025 events to spotlighting the use of AI in cancer research and care. Brought to you by CBIIT and NCI’s Division of Cancer Treatment and Diagnosis AI working group, the upcoming webinars will explore a variety of questions, such as the following:

• How can we use AI for diagnosis, treatment, drug development, and omics research?
• What are the related laws and ethical considerations for AI?
• How can we empower an AI-ready cancer research community through workforce development, collaborations, and funding?

To view upcoming speakers or recordings of past presentations, visit the CBIIT Data Science Seminar Series webpage.