S1, E21 - Jeff Chuang, PhD, The Jackson Laboratory

I was honored to join Steve Labkoff and Leon Rozenblit for the Practical AI in Healthcare podcast to discuss how image analysis is transforming cancer diagnosis and care, including our work on improving the process of diagnosing rare pediatric cancers.
open.spotify.com/episode/5NQX...

Emerging AI Approaches for Cancer Spatial Omics Abstract. Technological breakthroughs in spatial omics and artificial intelligence (AI) have the potential to transform the understanding of cancer cells a

I am excited to announce a new review by Javad Noorbakhsh, Ali Foroughi pour, and myself on Emerging AI Approaches for Cancer Spatial Omics, published in GigaScience. We discuss concepts important for the development of this fast moving field.
doi.org/10.1093/giga...

Eye on AI: How Artificial Intelligence Could Transform Care for Children with Sarcoma New AI-driven models unveiled at the AACR Annual Meeting 2025 could revolutionize how we diagnose pediatric sarcomas.

AACR story about our team's work on sarcoma diagnosis from histology images. www.aacr.org/blog/2025/07...

Multicenter Histology Image Integration and Multiscale Deep Learning for Machine Learning-Enabled Pediatric Sarcoma Classification Purpose Pediatric sarcomas are rare and diverse, often leading to misclassification that hampers prognosis and treatment planning. We collected and harmonized histology images from multiple medical ce...

My terrific student Adam Thiesen has a preprint up on Multicenter Histology Image Integration and Multiscale Deep Learning for Machine Learning-Enabled Pediatric Sarcoma Classification. This work was led by Jill Rubinstein , in collab with teams at JAX, Yale, MGH, and Penn. doi.org/10.1101/2025...

Emerging AI Approaches for Cancer Spatial Omics Technological breakthroughs in spatial omics and artificial intelligence (AI) have the potential to transform the understanding of cancer cells and the tumor microenvironment. Here we review the role ...

My colleagues Javad Noorbakhsh, Ali Foroughi pour and I have posted a preprint of a review summarizing Emerging AI Approaches for Cancer Spatial Omics. arxiv.org/abs/2506.23857

Belated congratulations to my MD/PhD student Adam Thiesen for being selected for the newsworthy article session at the AACR 2025 meeting on his work "Multicenter Histology Image Integration and Multiscale Deep Learning for Machine Learning-Enabled Pediatric Sarcoma Classification."

Thanks to all who came by the poster for my PhD student Sam Liu on "Spatially Resolved Immunologic Hallmarks of Response to Neoadjuvant Immune Checkpoint Blockade in Metastatic Melanoma" at AACR 2025. We are excited about this work with our collaborator Pei-Ling Chen from Moffitt Cancer Center.

Great job by Jie Zhou, an outstanding student about to graduate with her PhD from my lab, for her poster at AACR 2025. Thanks to all who came to her poster on "Unveiling the spatial landscape of tumor and stroma heterogeneity in colorectal cancer with spatial transcriptomics and deep learning"

Thanks to my colleagues at the PDXNet Annual Meeting last week in Chicago! It was an incredibly valuable discussion on new cancer treatment letters of intent coming out of patient-derived xenografts research, as well as basic research important to the use of these model systems.

Tissue AI: The future of tumor imaging Tissue AI is like upgrading from a paper atlas to a high-resolution, interactive GPS system. Traditional imaging methods are like a basic street map—outlining major landmarks but missing the fine deta...

For a great summary of how Tissue AI is revolutionizing the field of biology and especially cancer, check out this writeup of the science in my lab and others at The Jackson Laboratory. www.jax.org/news-and-ins...

Congrats to my amazing grad student Adam Thiesen for getting a podium talk at the Society for Surgical Oncology meeting, mentored by Dr. Jill Rubinstein. He’s speaking today on Deep Learning for Pediatric Rhabdomyosarcoma Subtype Classification from Histology Images.