research
∙
08/29/2023
A General-Purpose Self-Supervised Model for Computational Pathology
Tissue phenotyping is a fundamental computational pathology (CPath) task...
share
research
∙
07/27/2023
Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples
Human tissue and its constituent cells form a microenvironment that is f...
research
∙
07/24/2023
Towards a Visual-Language Foundation Model for Computational Pathology
The accelerated adoption of digital pathology and advances in deep learn...
research
∙
06/13/2023
Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images
Contrastive visual language pretraining has emerged as a powerful method...
research
∙
06/17/2022
Incorporating intratumoral heterogeneity into weakly-supervised deep learning models via variance pooling
Supervised learning tasks such as cancer survival prediction from gigapi...
research
∙
04/26/2022
Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images
Multiple Instance Learning (MIL) methods have become increasingly popula...
research
∙
10/01/2021
Algorithm Fairness in AI for Medicine and Healthcare
In the current development and deployment of many artificial intelligenc...
research
∙
08/04/2021
Pan-Cancer Integrative Histology-Genomic Analysis via Interpretable Multimodal Deep Learning
The rapidly emerging field of deep learning-based computational patholog...
research
∙
07/28/2021
Fast and Scalable Image Search For Histology
The expanding adoption of digital pathology has enabled the curation of ...
research
∙
07/27/2021
Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks
Cancer prognostication is a challenging task in computational pathology ...
research
∙
07/25/2021
Deep Learning-based Frozen Section to FFPE Translation
Frozen sectioning (FS) is the preparation method of choice for microscop...
research
∙
09/21/2020
Federated Learning for Computational Pathology on Gigapixel Whole Slide Images
Deep Learning-based computational pathology algorithms have demonstrated...
research
∙
06/24/2020
Deep Learning-based Computational Pathology Predicts Origins for Cancers of Unknown Primary
Cancers of unknown primary (CUP), represent 1-3 enigmatic disease where ...
research
∙
04/20/2020
Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images
The rapidly emerging field of computational pathology has the potential ...
research
∙
12/18/2019
Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis
Cancer diagnosis, prognosis and therapeutic response predictions are bas...
research
∙
12/11/2018
A flat persistence diagram for improved visualization of persistent homology
Visualization in the emerging field of topological data analysis has pro...
research
∙
12/11/2018