AIMC Topic: Diabetic Nephropathies
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MASP-2 deficiency does not prevent the progression of diabetic kidney disease in a mouse model of type 1 diabetes.
Scandinavian journal of immunology
Dec 25, 2023
Mannan-binding lectin (MBL) initiates the lectin pathway of complement and has been linked to albuminuria and mortality in diabetes. We hypothesize that MBL-associated serine protease 2 (MASP-2) deficiency will protect against diabetes-induced kidney...
Machine learning prediction models for diabetic kidney disease: systematic review and meta-analysis.
Endocrine
Dec 23, 2023
BACKGROUND: Machine learning is increasingly recognized as a viable approach for identifying risk factors associated with diabetic kidney disease (DKD). However, the current state of real-world research lacks a comprehensive systematic analysis of th...
Development of an automated estimation of foot process width using deep learning in kidney biopsies from patients with Fabry, minimal change, and diabetic kidney diseases.
Kidney international
Sep 27, 2023
Podocyte injury plays a key role in pathogenesis of many kidney diseases with increased podocyte foot process width (FPW), an important measure of podocyte injury. Unfortunately, there is no consensus on the best way to estimate FPW and unbiased ster...
Intelligent Algorithm-Based Ultrasound Image for Evaluating the Effect of Comprehensive Nursing Scheme on Patients with Diabetic Kidney Disease.
Computational and mathematical methods in medicine
Mar 10, 2022
This study was aimed at exploring the effect of ultrasound image evaluation of comprehensive nursing scheme based on artificial intelligence algorithms on patients with diabetic kidney disease (DKD). 44 patients diagnosed with DKD were randomly divid...
Systems biology and machine learning approaches identify drug targets in diabetic nephropathy.
Scientific reports
Dec 6, 2021
Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the underlying mechanisms have not yet been comprehensively understood. In this study, a systematic appr...
Drug Design
Gene Expression Profiling
Gene Regulatory Networks
Mice
Algorithms
Animals
Male
Global Health
Signal Transduction
Support Vector Machine
Cluster Analysis
MicroRNAs
Regression Analysis
Diabetic Nephropathies
Computational Biology
Systems Biology
Epigenesis, Genetic
Humans
Machine Learning
Principal Component Analysis
Linear Models
Oligonucleotide Array Sequence Analysis
Chemistry, Pharmaceutical
Mice, Inbred DBA
Microarray Analysis
Kidney Cortex
Kidney Medulla
Risk prediction of diabetic nephropathy using machine learning techniques: A pilot study with secondary data.
Diabetes & metabolic syndrome
Aug 28, 2021
AIMS: This research work presented a comparative study of machine learning (ML), including two objectives: (i) determination of the risk factors of diabetic nephropathy (DN) based on principal component analysis (PCA) via different cutoffs; (ii) pred...
A New Clinical Utility for Tubular Markers to Identify Kidney Responders to Saxagliptin Treatment in Adults With Diabetic Nephropathy.
Canadian journal of diabetes
Aug 2, 2021
OBJECTIVES: In recent clinical studies, saxagliptin exhibited nephroprotective potential by lowering albuminuria. In this study, we aimed to determine whether these kidney effects of saxagliptin were mediated by changes in markers of kidney tubular d...
Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict progression of diabetic kidney disease.
Diabetologia
Apr 2, 2021
AIM: Predicting progression in diabetic kidney disease (DKD) is critical to improving outcomes. We sought to develop/validate a machine-learned, prognostic risk score (KidneyIntelX™) combining electronic health records (EHR) and biomarkers.
Artificial intelligence predicts the progression of diabetic kidney disease using big data machine learning.
Scientific reports
Aug 14, 2019
Artificial intelligence (AI) is expected to support clinical judgement in medicine. We constructed a new predictive model for diabetic kidney diseases (DKD) using AI, processing natural language and longitudinal data with big data machine learning, b...
Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.
Clinical and translational science
May 31, 2019
Applying data mining and machine learning (ML) techniques to clinical data might identify predictive biomarkers for diabetic nephropathy (DN), a common complication of type 2 diabetes mellitus (T2DM). A retrospective analysis of the Action to Control...
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