10 citations · 11 across the 5 of their papers we have counts for
6 papers
When Riemann flows with Wasserstein: Generative Modeling of Probability Distributions on Manifolds
Doron Haviv, Edward De Brouwer, Rishabh Anand +4
Many scientific datasets, such as molecular conformational ensembles or single-cell tissue measurements, are naturally modeled as meta-distributions: distributions over probability…
Development and Validation of a Deep Learning-Based Microsatellite Instability Predictor from Prostate Cancer Whole-Slide Images
Qiyuan Hu, Abbas A. Rizvi, Geoffery Schau +13
Microsatellite instability-high (MSI-H) is a tumor agnostic biomarker for immune checkpoint inhibitor therapy. However, MSI status is not routinely tested in prostate cancer, in pa…
Prediction of MET Overexpression in Non-Small Cell Lung Adenocarcinomas from Hematoxylin and Eosin Images
Kshitij Ingale, Sun Hae Hong, Josh S. K. Bell +8
MET protein overexpression is a targetable event in non-small cell lung cancer (NSCLC) and is the subject of active drug development. Challenges in identifying patients for these t…
AI-augmented histopathologic review using image analysis to optimize DNA yield and tumor purity from FFPE slides
Bolesław L. Osinski, Aïcha BenTaieb, Irvin Ho +8
To achieve minimum DNA input and tumor purity requirements for next-generation sequencing (NGS), pathologists visually estimate macrodissection and slide count decisions. Misestima…
Deep Learning Models for Digital Pathology
Aïcha BenTaieb, Ghassan Hamarneh
Histopathology images; microscopy images of stained tissue biopsies contain fundamental prognostic information that forms the foundation of pathological analysis and diagnostic med…
Select, Attend, and Transfer: Light, Learnable Skip Connections
Saeid Asgari Taghanaki, Aicha Bentaieb, Anmol Sharma +8
Skip connections in deep networks have improved both segmentation and classification performance by facilitating the training of deeper network architectures, and reducing the risk…