activity
20172026
most citedAutomated Diagnosis of Lymphoma with Digital Pathology Images Using Deep Learning

48 citations · 49 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Artificial intelligence application in lymphoma diagnosis with Vision Transformer using weakly supervised training

Nghia, Nguyen, Amer Wahed +9

Vision transformers (ViT) have been shown to allow for more flexible feature detection and can outperform convolutional neural network (CNN) when pre-trained on sufficient data. Du…

cs.CV2025

Artificial intelligence application in lymphoma diagnosis: from Convolutional Neural Network to Vision Transformer

Daniel Rivera, Jacob Huddin, Alexander Banerjee +6

Recently, vision transformers were shown to be capable of outperforming convolutional neural networks when pretrained on sufficiently large datasets. Vision transformer models show…

cs.HC2024

Telepathology in Hematopathology Diagnostics: A Collaboration Between Ho Chi Minh City Oncology Hospital and University of Texas Health-McGovern Medical School

Uyen Ly, Quang Nguyen, Dang Nguyen +7

Digital pathology in the form of whole-slide-imaging has been used to support diagnostic consultation through telepathology. Previous studies have mostly addressed the technical as…

cs.CV2023★ 1 cited

Deep Learning Provides Rapid Screen for Breast Cancer Metastasis with Sentinel Lymph Nodes

Kareem Allam, Xiaohong Iris Wang, Songlin Zhang +6

Deep learning has been shown to be useful to detect breast cancer metastases by analyzing whole slide images of sentinel lymph nodes. However, it requires extensive scanning and an…

cs.CV2018★ 48 cited

Automated Diagnosis of Lymphoma with Digital Pathology Images Using Deep Learning

Hanadi El Achi, Tatiana Belousova, Lei Chen +6

Recent studies have shown promising results in using Deep Learning to detect malignancy in whole slide imaging. However, they were limited to just predicting positive or negative f…

q-bio.QM2017

Proteomics Analysis of FLT3-ITD Mutation in Acute Myeloid Leukemia Using Deep Learning Neural Network

Christine A. Liang, Lei Chen, Amer Wahed +1

Deep Learning can significantly benefit cancer proteomics and genomics. In this study, we attempt to determine a set of critical proteins that are associated with the FLT3-ITD muta…