Nephrology

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

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BiM-GeoAttn-Net: Linear-Time Depth Modeling with Geometry-Aware Attention for 3D Aortic Dissection CTA Segmentation

Accurate segmentation of aortic dissection (AD) lumens in CT angiography (CTA) is essential for quan...

CT-based Automated Volumetry as a Biomarker of Global and Split Renal Function in Living Kidney Donors

Background: Kidney volumetry derived from CT has been proposed as a surrogate of renal function in l...

Machine learning-based prediction of cardiovascular disease risk in Africa using WHO Stepwise Surveys: 2014-2019

Introduction: Cardiovascular diseases (CVDs) are the leading cause of death globally, with rising bu...

A Data-Driven Approach to Support Clinical Renal Replacement Therapy

This study investigates a data-driven machine learning approach to predict membrane fouling in criti...

Enhancing Renal Tumor Malignancy Prediction: Deep Learning with Automatic 3D CT Organ Focused Attention

Accurate prediction of malignancy in renal tumors is crucial for informing clinical decisions and op...

Large-Language Models for data extraction from written kidney biopsy reports

Introduction: Kidney biopsy reports contain rich information that is clinically actionable and usefu...

Inference of cancer driver mutations from tumor microenvironmentcomposition: a pan-cancer study with cross-platform external validation

Cancer driver mutations shape the tumor microenvironment (TME), yet whether TME composition alone ca...

AI-DRIVEN DIAGNOSIS OF NON-ALCOHOLIC FATTY LIVER DISEASE AND ASSOCIATED COMORBIDITIES

Non-alcoholic fatty liver disease (NAFLD) is a globally prevalent hepatic condition caused by the bu...

Comparing Modelling Architectures in the context of EGFR Status Classification in Non Small Cell Lung Cancer

Radiogenomics enables the non invasive characterisation of the genomic and molecular properties of t...

High-Resolution 3D Histology of the Murine Kidney Using Synchrotron X-Ray Micro-CT

Conventional two-dimensional (2D) histology relies upon destructive sample preparation and stereolog...

UCSF RMaC: University of California San Francisco 3D Multi-Phase Renal Mass CT Dataset with Tumor Segmentations

Current standard of care imaging practices cannot reliably differentiate among certain renal tumors ...

Identifying Reasons for ACEI/ARB Non-Use in CKD Using Scalable Clinical NLP with Schema-Guided LLM Augmentation

IMPORTANCE: Although angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor block...

AMAP-APP: Efficient Segmentation and Morphometry Quantification of Fluorescent Microscopy Images of Podocytes

Background: Automated podocyte foot process quantification is vital for kidney research, but the est...

LLM-based reconstruction of longitudinal clinical trajectories in chronic liver disease.

Background: Liver cancer primarily develops in patients with chronic liver disease (CLD), yet most c...

Interpretable machine learning model for predicting kidney failure among CAKUT children in multicenter large-scale study

Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidn...

Decoding Future Risk: Deep Learning Analysis of Tubular Adenoma Whole-Slide Images

Colorectal cancer (CRC) remains a significant cause of cancer-related mortality, despite the widespr...

Single center Automated, Multi-Source deeply Phenotyped Heart Transplant Registry as a template to build tailored data infrastructure

Background: Traditional heart transplant registries often lack the granularity required for deep phe...

Active Label Cleaning for Reliable Detection of Electron Dense Deposits in Transmission Electron Microscopy Images

Automated detection of electron dense deposits (EDD) in glomerular disease is hindered by the scarci...

Personalised approach to hypertension treatment: Rationale and design of the HYPERMARKER randomised trial

Background and Objective: Blood pressure treatment response is variable in individual patients, and ...

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