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...
share
research
∙
06/06/2022
Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning
Vision Transformers (ViTs) and their multi-scale and hierarchical variat...
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