High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models. - James Monaco; John Tomaszewski 001; Michael D. Feldman; Ian S. Hagemann; Mehdi Moradi; Parvin Mousavi; Alexander Boag; Chris Davidson; Purang Abolmaesumi; Anant Madabhushi (Medical Image Anal., 2010)

In-laboratory breast specimen radiography reduces tissue block utilization and improves turnaround time of pathologic examination. - Sri Krishna Chaitanya Arudra; Laura C. Garvey; Ian S. Hagemann (BMC Medical Imaging, 2021)

Weakly supervised deep learning for predicting the response to hormonal treatment of women with atypical endometrial hyperplasia: a feasibility study. - Seyed M. M. Kahaki; Ian S. Hagemann; Kenny H. Cha; Christopher J. Trindade; Nicholas Petrick; Nicolas Kostelecky; Weijie Chen 007 (Digital and Computational Pathology, 2023)

Contextual Unsupervised Deep Clustering in Digital Pathology. - Mariia Sidulova; Seyed Kahaki; Ian S. Hagemann; Alexej Gossmann (CHIL, 2024)