Liang Cheng: AI Applications in Pathology
Liang Cheng, Vice Chair for Translational Research at Warren Alpert Medical School of Brown University, President of the International Society of Urologic Pathology, posted on LinkedIn:
“Published on July 2, 2025 in JCO Clinical Cancer Informatics!
I’m delighted to share our latest work on AI Applications in Pathology. Congratulations to Drs. Zhu, Chen, and our entire team! The capability to procure pathologic images containing specific histopathologic features may aid in synthesizing images of rare pathologic subtypes, which are often underrepresented in existing data sets.
By generating realistic images of these rare subtypes, DALL.E 3 may potentially enrich the training sets for AI pathology diagnostic models, improving their ability to recognize and diagnose uncommon pathologies. This could lead to more comprehensive and robust AI tools for pathology training and education.
Our study also underscores the growing challenge posed by highly realistic AI-generated images in medicine. As these technologies evolve, collaboration between academic centers and industry will be essential to ensure their ethical and responsible use.”
Title: Clinical Application of Large Language Models in Generating Pathologic Images
Authors: Lingxuan Zhu, Yancheng Lai, Na Ta, Weiming Mou, Rodolfo Montironi, Katrina Collins, Kenneth A. Iczkowski, Fei Chen, Antonio Lopez-Beltran, Rui Zhou, Huang He, Gyan Pareek, Elias Hyams, Dragan Golijanin, Sari Khaleel, Borivoj Golijanin, Kamil Malshy, Alessia Cimadamore, Xiang Ni, Tao Yang, Liang Cheng, Rui Chen
Read The Full Article at JCO Clinical Cancer Informatics.
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