Nephrology

Latest AI and machine learning research in nephrology for healthcare professionals.

4,989 articles
Stay Ahead - Weekly Nephrology research updates
Subscribe
Browse Categories
Showing 3403-3423 of 4,989 articles
Applying Artificial Intelligence to Quantify Body Composition on Abdominal CTs and Better Predict Kidney Transplantation Wait-List Mortality.

BACKGROUND: Prekidney transplant evaluation routinely includes abdominal CT for presurgical vascular...

Mar 2025 40044312
A Machine Learning Model for Diagnosing Opportunistic Infections in HIV Patients: Broad Applicability Across Infection Types.

Opportunistic infections (OIs) are the leading cause of hospitalisation and mortality among Human Im...

Mar 2025 40122698
Ethical considerations on the use of big data and artificial intelligence in kidney research from the ERA ethics committee.

In the current paper, we will focus on requirements to ensure big data can advance the outcomes of o...

Feb 2025 39572076
3D Nephrographic Image Synthesis in CT Urography with the Diffusion Model and Swin Transformer

Purpose: This study aims to develop and validate a method for synthesizing 3D nephrographic phase ...

Med-gte-hybrid: A contextual embedding transformer model for extracting actionable information from clinical texts

We introduce a novel contextual embedding model med-gte-hybrid that was derived from the gte-large...

The ETKidney simulator: a discrete event simulator to assess the impact of alternative kidney allocation rules in Eurotransplant

Over 10,000 candidates wait for a kidney transplantation in Eurotransplant, and are prioritized fo...

LIDDIA: Language-based Intelligent Drug Discovery Agent

Drug discovery is a long, expensive, and complex process, relying heavily on human medicinal chemi...

GraphMorph: Tubular Structure Extraction by Morphing Predicted Graphs

Accurately restoring topology is both challenging and crucial in tubular structure extraction task...

Detection and classification of glomerular lesions in kidney graft biopsies using 2-stage deep learning approach.

Acute allograft rejection in patients undergoing renal transplantation is diagnosed through histopat...

Feb 2025 39960931
Evaluation of risk factors for thromboembolic events in multiple myeloma patients using multiple machine learning models.

Venous thromboembolic events (VTE) is a frequent complication in multiple myeloma (MM) patients, rai...

Feb 2025 39960959
KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level

Chronic kidney disease (CKD) is a major global health issue, affecting over 10% of the population ...

Choroidal image analysis for OCT image sequences with applications in systemic health

The choroid, a highly vascular layer behind the retina, is an extension of the central nervous sys...

Proprioceptive Origami Manipulator

Origami offers a versatile framework for designing morphable structures and soft robots by exploit...

Evaluation of Vision Transformers for Multimodal Image Classification: A Case Study on Brain, Lung, and Kidney Tumors

Neural networks have become the standard technique for medical diagnostics, especially in cancer d...

Towards Fine-grained Renal Vasculature Segmentation: Full-Scale Hierarchical Learning with FH-Seg

Accurate fine-grained segmentation of the renal vasculature is critical for nephrological analysis...

Differentiating between renal medullary and clear cell renal carcinoma with a machine learning radiomics approach.

BACKGROUND: The objective of this study was to develop and validate a radiomics-based machine learni...

Feb 2025 39963829
Hybrid Deep Learning Framework for Classification of Kidney CT Images: Diagnosis of Stones, Cysts, and Tumors

Medical image classification is a vital research area that utilizes advanced computational techniq...

INST-Sculpt: Interactive Stroke-based Neural SDF Sculpting

Recent advances in implicit neural representations have made them a popular choice for modeling 3D...

Causally-informed Deep Learning towards Explainable and Generalizable Outcomes Prediction in Critical Care

Recent advances in deep learning (DL) have prompted the development of high-performing early warni...

Browse Categories