4 citations · 8 across the 6 of their papers we have counts for
6 papers
Graph Laplacian Transformer with Progressive Sampling for Prostate Cancer Grading
Masum Shah Junayed, John Derek Van Vessem, Qian Wan +2
Prostate cancer grading from whole-slide images (WSIs) remains a challenging task due to the large-scale nature of WSIs, the presence of heterogeneous tissue structures, and diffic…
Robust Training with Data Augmentation for Medical Imaging Classification
Josué Martínez-Martínez, Olivia Brown, Mostafa Karami +1
Deep neural networks are increasingly being used to detect and diagnose medical conditions using medical imaging. Despite their utility, these models are highly vulnerable to adver…
Multi-modal Spatial Clustering for Spatial Transcriptomics Utilizing High-resolution Histology Images
Bingjun Li, Mostafa Karami, Masum Shah Junayed +1
Understanding the intricate cellular environment within biological tissues is crucial for uncovering insights into complex biological functions. While single-cell RNA sequencing ha…
Unsupversied feature correlation model to predict breast abnormal variation maps in longitudinal mammograms
Jun Bai, Annie Jin, Madison Adams +2
Breast cancer continues to be a significant cause of mortality among women globally. Timely identification and precise diagnosis of breast abnormalities are critical for enhancing…
A Multimodal Graph Neural Network Framework of Cancer Molecular Subtype Classification
Bingjun Li, Sheida Nabavi
The recent development of high-throughput sequencing creates a large collection of multi-omics data, which enables researchers to better investigate cancer molecular profiles and c…
Weakly-Supervised Deep Learning Model for Prostate Cancer Diagnosis and Gleason Grading of Histopathology Images
Mohammad Mahdi Behzadi, Mohammad Madani, Hanzhang Wang +6
Prostate cancer is the most common cancer in men worldwide and the second leading cause of cancer death in the United States. One of the prognostic features in prostate cancer is t…