His research focuses on the invention and application of computational techniques to advance cancer diagnostics, prognostics, and therapeutics.
Three pillars of his research are 1) pathology image analysis, 2) tumor microenvironment profiling, and 3) imaging, clinical data, and multi-omics integration.
Dr. Chen aims to harmonize the perspectives of pathologists, oncologists, biologists, and computer scientists toward developing robust solutions to address critical unmet needs for making cancer history.
Pingjun Chen*, Siba El Hussein*, et al.,
Chronic Lymphocytic Leukemia Progression Diagnosis with Intrinsic Cellular Patterns via Unsupervised Clustering,
in Cancers, 2022.
Siba El Hussein*, Pingjun Chen*, et al.,
Artificial Intelligence-Assisted Mapping of Proliferation Centers Allows the Distinction of Accelerated Phase from Large Cell Transformation in Chronic Lymphocytic Leukemia,
in Modern Pathology, 2022.
Monthly Readers' Choice
Siba El Hussein*, Pingjun Chen*, et al.,
Artificial Intelligence Strategy Integrating Morphologic and Architectural Biomarkers Provides Robust Diagnostic Accuracy for Disease Progression in Chronic Lymphocytic Leukemia,
in The Journal of Pathology, 2021.
Invited Commentary
Joseph D. Khoury, Jia Wu, Siba EI Hussein & Pingjun Chen,
Methods and Systems for Determining Leukemia or Lymphoma Levels using Lymphoid Images, 2023. Filed.
Shanhui Sun, Pingjun Chen, Xiao Chen, Zhang Chen & Terrence Chen,
Systems and Methods for Image Segmentation, 2022.
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