198 citations · 307 across the 14 of their papers we have counts for
14 papers
Predicting Targeted Therapy Resistance in Non-Small Cell Lung Cancer Using Multimodal Machine Learning
Peiying Hua, Andrea Olofson, Faraz Farhadi +7
Lung cancer is the primary cause of cancer death globally, with non-small cell lung cancer (NSCLC) emerging as its most prevalent subtype. Among NSCLC patients, approximately 32.3%…
Improving Colorectal Cancer Screening and Risk Assessment through Predictive Modeling on Medical Images and Records
Shuai Jiang, Christina Robinson, Joseph Anderson +4
Colonoscopy screening effectively identifies and removes polyps before they progress to colorectal cancer (CRC), but current follow-up guidelines rely primarily on histopathologica…
Masked Pre-Training of Transformers for Histology Image Analysis
Shuai Jiang, Liesbeth Hondelink, Arief A. Suriawinata +1
In digital pathology, whole slide images (WSIs) are widely used for applications such as cancer diagnosis and prognosis prediction. Visual transformer models have recently emerged…
MHAttnSurv: Multi-Head Attention for Survival Prediction Using Whole-Slide Pathology Images
Shuai Jiang, Arief A. Suriawinata, Saeed Hassanpour
In pathology, whole-slide images (WSI) based survival prediction has attracted increasing interest. However, given the large size of WSIs and the lack of pathologist annotations, e…
Resolution-Based Distillation for Efficient Histology Image Classification
Joseph DiPalma, Arief A. Suriawinata, Laura J. Tafe +2
Developing deep learning models to analyze histology images has been computationally challenging, as the massive size of the images causes excessive strain on all parts of the comp…
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…
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
Jerry Wei, Arief Suriawinata, Bing Ren +10
Applying curriculum learning requires both a range of difficulty in data and a method for determining the difficulty of examples. In many tasks, however, satisfying these requireme…
Difficulty Translation in Histopathology Images
Jerry Wei, Arief Suriawinata, Xiaoying Liu +5
The unique nature of histopathology images opens the door to domain-specific formulations of image translation models. We propose a difficulty translation model that modifies color…
Predicting colorectal polyp recurrence using time-to-event analysis of medical records
Lia X. Harrington, Jason W. Wei, Arief A. Suriawinata +2
Identifying patient characteristics that influence the rate of colorectal polyp recurrence can provide important insights into which patients are at higher risk for recurrence. We…
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…
Deep neural networks for automated classification of colorectal polyps on histopathology slides: A multi-institutional evaluation
Jason W. Wei, Arief A. Suriawinata, Louis J. Vaickus +10
Histological classification of colorectal polyps plays a critical role in both screening for colorectal cancer and care of affected patients. An accurate and automated algorithm fo…
Automated detection of celiac disease on duodenal biopsy slides: a deep learning approach
Jason W. Wei, Jerry W. Wei, Christopher R. Jackson +3
Celiac disease prevalence and diagnosis have increased substantially in recent years. The current gold standard for celiac disease confirmation is visual examination of duodenal mu…
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…
Deep-Learning for Classification of Colorectal Polyps on Whole-Slide Images
Bruno Korbar, Andrea M. Olofson, Allen P. Miraflor +5
Histopathological characterization of colorectal polyps is an important principle for determining the risk of colorectal cancer and future rates of surveillance for patients. This…