AIMC Topic: Proteinuria
Clear Filters Showing 1 to 10 of 20 articles
"Three-in-one" Analysis of Proteinuria for Disease Diagnosis through Multifunctional Nanoparticles and Machine Learning.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Jan 15, 2025
Urinalysis is one of the predominant tools for clinical testing owing to the abundant composition, sufficient volume, and non-invasive acquisition of urine. As a critical component of routine urinalysis, urine protein testing measures the levels and ...
Multi-stain deep learning prediction model of treatment response in lupus nephritis based on renal histopathology.
Kidney international
Dec 27, 2024
The response of the kidney after induction treatment is one of the determinants of prognosis in lupus nephritis, but effective predictive tools are lacking. Here, we sought to apply deep learning approaches on kidney biopsies for treatment response p...
Development of a machine learning tool to predict the risk of incident chronic kidney disease using health examination data.
Frontiers in public health
Nov 1, 2024
BACKGROUND: Chronic kidney disease (CKD) is characterized by a decreased glomerular filtration rate or renal injury (especially proteinuria) for at least 3 months. The early detection and treatment of CKD, a major global public health concern, before...
Effects of tacrolimus on proteinuria in Chinese and Indian patients with idiopathic membranous nephropathy: the results of machine learning study.
International urology and nephrology
Apr 20, 2024
PURPOSE: The present study aims to explore the effects of tacrolimus on proteinuria in patients with idiopathic membranous nephropathy (IMN) and recommend an appropriate dosage schedule via machine learning method.
Machine learning application identifies plasma markers for proteinuria in metastatic colorectal cancer patients treated with Bevacizumab.
Cancer chemotherapy and pharmacology
Feb 25, 2024
BACKGROUND AND OBJECTIVES: Proteinuria is a common complication after the application of bevacizumab therapy in patients with metastatic colorectal cancer, and severe proteinuria can lead to discontinuation of the drug. There is a lack of sophisticat...
Deep learning analysis of clinical course of primary nephrotic syndrome: Japan Nephrotic Syndrome Cohort Study (JNSCS).
Clinical and experimental nephrology
Aug 12, 2022
BACKGROUND: Prognosis of nephrotic syndrome has been evaluated based on pathological diagnosis, whereas its clinical course is monitored using objective items and the treatment strategy is largely the same. We examined whether the entire natural hist...
Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study.
The Lancet. Digital health
Oct 28, 2021
BACKGROUND: Kidney allograft failure is a common cause of end-stage renal disease. We aimed to develop a dynamic artificial intelligence approach to enhance risk stratification for kidney transplant recipients by generating continuously refined predi...
Artificial Intelligence
Kidney Transplantation
Prognosis
Humans
Area Under Curve
Bayes Theorem
Middle Aged
Models, Biological
Risk Assessment
Proteinuria
Postoperative Complications
Allografts
Transplant Recipients
Kidney
Female
Renal Insufficiency
Glomerular Filtration Rate
Reproducibility of Results
Adult
Male
COVID-19 and the kidney: A retrospective analysis of 37 critically ill patients using machine learning.
PloS one
May 20, 2021
INTRODUCTION: There is evidence that SARS-CoV2 has a particular affinity for kidney tissue and is often associated with kidney failure.
Risk stratification for mortality in cardiovascular disease survivors: A survival conditional inference tree analysis.
Nutrition, metabolism, and cardiovascular diseases : NMCD
Oct 3, 2020
BACKGROUND AND AIMS: Efficient analysis strategies for complex network with cardiovascular disease (CVD) risk stratification remain lacking. We sought to identify an optimized model to study CVD prognosis using survival conditional inference tree (SC...
Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database.
PloS one
Sep 17, 2020
Artificial intelligence is increasingly being adopted in medical fields to predict various outcomes. In particular, chronic kidney disease (CKD) is problematic because it often progresses to end-stage kidney disease. However, the trajectories of kidn...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823