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04/14/2023
Masked Pre-Training of Transformers for Histology Image Analysis
In digital pathology, whole slide images (WSIs) are widely used for appl...
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09/13/2022
HistoPerm: A Permutation-Based View Generation Approach for Learning Histopathologic Feature Representations
Recently, deep learning methods have been successfully applied to solve ...
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05/24/2022
Interpretation Quality Score for Measuring the Quality of interpretability methods
Machine learning (ML) models have been applied to a wide range of natura...
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03/30/2022
Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning
Artificial intelligence, particularly through recent advancements in dee...
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01/28/2022
Calibrating Histopathology Image Classifiers using Label Smoothing
The classification of histopathology images fundamentally differs from t...
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10/22/2021
MHAttnSurv: Multi-Head Attention for Survival Prediction Using Whole-Slide Pathology Images
In pathology, whole-slide images (WSI) based survival prediction has att...
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01/29/2021
A Petri Dish for Histopathology Image Analysis
With the rise of deep learning, there has been increased interest in usi...
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01/11/2021
Resolution-Based Distillation for Efficient Histology Image Classification
Developing deep learning models to analyze histology images has been com...
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10/30/2020
Development and Evaluation of a Deep Neural Network for Histologic Classification of Renal Cell Carcinoma on Biopsy and Surgical Resection Slides
Renal cell carcinoma (RCC) is the most common renal cancer in adults. Th...
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09/29/2020
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
Applying curriculum learning requires both a range of difficulty in data...
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04/27/2020
Difficulty Translation in Histopathology Images
The unique nature of histopathology images opens the door to domain-spec...
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04/14/2020
Multi-Ontology Refined Embeddings (MORE): A Hybrid Multi-Ontology and Corpus-based Semantic Representation for Biomedical Concepts
Objective: Currently, a major limitation for natural language processing...
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12/05/2019
Self-Supervised Contextual Language Representation of Radiology Reports to Improve the Identification of Communication Urgency
Machine learning methods have recently achieved high-performance in biom...
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11/26/2019
Artificial Intelligence for Diagnosis of Skin Cancer: Challenges and Opportunities
Recently, there has been great interest in developing Artificial Intelli...
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11/25/2019
Automatic Post-Stroke Lesion Segmentation on MR Images using 3D Residual Convolutional Neural Network
In this paper, we demonstrate the feasibility and performance of deep re...
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11/18/2019
Predicting colorectal polyp recurrence using time-to-event analysis of medical records
Identifying patient characteristics that influence the rate of colorecta...
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10/13/2019
Generative Image Translation for Data Augmentation in Colorectal Histopathology Images
We present an image translation approach to generate augmented data for ...
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09/27/2019
Deep neural networks for automated classification of colorectal polyps on histopathology slides: A multi-institutional evaluation
Histological classification of colorectal polyps plays a critical role i...
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01/31/2019
Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks
Classification of histologic patterns in lung adenocarcinoma is critical...
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01/31/2019
Automated detection of celiac disease on duodenal biopsy slides: a deep learning approach
Celiac disease prevalence and diagnosis have increased substantially in ...
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11/20/2018
Finding a Needle in the Haystack: Attention-Based Classification of High Resolution Microscopy Images
Deep learning for classification of microscopy images is challenging bec...
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03/05/2017