output
20142024
most citedAttention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides

198 citations

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Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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eess.IV2024★ 13 cited

AI Workflow, External Validation, and Development in Eye Disease Diagnosis

Qingyu Chen, Tiarnan D L Keenan, Elvira Agron +35

Timely disease diagnosis is challenging due to increasing disease burdens and limited clinician availability. AI shows promise in diagnosis accuracy but faces real-world applicatio…

eess.IV2021★ 3 cited

A Petri Dish for Histopathology Image Analysis

Jerry Wei, Arief Suriawinata, Bing Ren +9

With the rise of deep learning, there has been increased interest in using neural networks for histopathology image analysis, a field that investigates the properties of biopsy or…

eess.IV2020★ 6 cited

Development and Evaluation of a Deep Neural Network for Histologic Classification of Renal Cell Carcinoma on Biopsy and Surgical Resection Slides

Mengdan Zhu, Bing Ren, Ryland Richards +3

Renal cell carcinoma (RCC) is the most common renal cancer in adults. The histopathologic classification of RCC is essential for diagnosis, prognosis, and management of patients. R…

eess.IV2019★ 49 cited

Generative Image Translation for Data Augmentation in Colorectal Histopathology Images

Jerry Wei, Arief Suriawinata, Louis Vaickus +4

We present an image translation approach to generate augmented data for mitigating data imbalances in a dataset of histopathology images of colorectal polyps, adenomatous tumors th…

eess.IV2018★ 198 cited

Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides

Naofumi Tomita, Behnaz Abdollahi, Jason Wei +3

Deep learning-based methods, such as the sliding window approach for cropped-image classification and heuristic aggregation for whole-slide inference, for analyzing histological pa…