Back to search

Article

Spatially Aware Transformer Networks for Contextual Prediction of Diabetic Nephropathy Progression from Whole Slide Images

2023-02-23

Abstract excerpt

<h4>ABSTRACT</h4> Diabetic nephropathy (DN) in the context of type 2 diabetes is the leading cause of end-stage renal disease (ESRD) in the United States. DN is graded based on glomerular morphology and has a spatially heterogeneous presentation in kidney biopsies that complicates pathologists’ predictions of disease progression. Artificial intelligence and deep learning methods for pathology have shown promise fo...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
fcdcff05-ae40-5c24-b2de-ac601ae99325
DOI
10.1101/2023.02.20.23286044
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Spatially Aware Transformer Networks for Contextual Prediction of Diabetic Nephropathy Progression from Whole Slide ImagesDOI 10.1101/2023.02.20.23286044
Discovery of Novel Digital Biomarkers for Type 2 Diabetic Nephropathy Classification via Integration of Urinary Proteomics and PathologySemantic proximity
Exploring the Mosaic-like Tissue Architecture of Kidney Diseases Using Relation Equivariant Graph Neural Networks on Spatially Resolved TranscriptomicsSemantic proximity
Transformer with convolution and graph-node co-embedding: An accurate and interpretable vision backbone for predicting gene expressions from local histopathological image.Semantic proximity
A spatially guided machine learning method to classify and quantify glomerular patterns of injury in histology imagesSemantic proximity
A Deep Learning-Based Tool for Segmentation and Quantification of i-IFTA, Focal Infiltrates, and Tubular Dilation in Haematoxylin-Eosin Stained Renal Whole-Slide ImagesSemantic proximity
scoMorphoFISH: A Deep-Learning enabled toolbox for single-cell single-mRNA quantification and correlative (ultra-)morphometrySemantic proximity
Deep Learning-Identified Clinical Trajectory Patterns and Associations with Kidney Outcomes in IgA NephropathySemantic proximity
High-dimensional spatial proteomics and novel machine learning pipeline identifies disease specific renal damage statesSemantic proximity
High-throughput image analysis with deep learning captures heterogeneity and spatial relationships after kidney injurySemantic proximity
Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location and histology using GCNSemantic proximity
Deep-learning Based Pathological Assessment of Frozen Procurement Kidney Biopsies Predicts Graft Loss and Guides Organ Utilization: A Large-scale Retrospective StudySemantic proximity
Phenotypic and prognostic insights through unbiased self-supervised learning on kidney histologySemantic proximity
Select a neighboring publication to make it the new centre.