AIMC Topic: Renal Insufficiency, Chronic
Clear Filters Showing 111 to 120 of 233 articles
Prediction of Incident Atrial Fibrillation in Chronic Kidney Disease: The Chronic Renal Insufficiency Cohort Study.
Clinical journal of the American Society of Nephrology : CJASN
Jul 12, 2021
BACKGROUND AND OBJECTIVES: Atrial fibrillation (AF) is common in CKD and associated with poor kidney and cardiovascular outcomes. Prediction models developed using novel methods may be useful to identify patients with CKD at highest risk of incident ...
Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.
Nature biomedical engineering
Jun 15, 2021
Regular screening for the early detection of common chronic diseases might benefit from the use of deep-learning approaches, particularly in resource-poor or remote settings. Here we show that deep-learning models can be used to identify chronic kidn...
Humans
Neural Networks, Computer
Disease Progression
Deep Learning
Blood Glucose
ROC Curve
Prospective Studies
Female
Male
Middle Aged
Retina
Body Height
Image Interpretation, Computer-Assisted
Metadata
Photography
Diabetes Mellitus, Type 2
Renal Insufficiency, Chronic
Glomerular Filtration Rate
Body Mass Index
Area Under Curve
Fundus Oculi
Body Weight
Diagnosis of Chronic Kidney Disease Using Effective Classification Algorithms and Recursive Feature Elimination Techniques.
Journal of healthcare engineering
Jun 9, 2021
Chronic kidney disease (CKD) is among the top 20 causes of death worldwide and affects approximately 10% of the world adult population. CKD is a disorder that disrupts normal kidney function. Due to the increasing number of people with CKD, effective...
Computational Models Used to Predict Cardiovascular Complications in Chronic Kidney Disease Patients: A Systematic Review.
Medicina (Kaunas, Lithuania)
May 27, 2021
cardiovascular complications (CVC) are the leading cause of death in patients with chronic kidney disease (CKD). Standard cardiovascular disease risk prediction models used in the general population are not validated in patients with CKD. We aim to ...
Health improvement framework for actionable treatment planning using a surrogate Bayesian model.
Nature communications
May 25, 2021
Clinical decision-making regarding treatments based on personal characteristics leads to effective health improvements. Machine learning (ML) has been the primary concern of diagnosis support according to comprehensive patient information. A prominen...
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.
Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning.
Laboratory investigation; a journal of technical methods and pathology
May 18, 2021
Delayed graft function (DGF) is a strong risk factor for development of interstitial fibrosis and tubular atrophy (IFTA) in kidney transplants. Quantitative assessment of inflammatory infiltrates in kidney biopsies of DGF patients can reveal predicti...
Construction data mining methods in the prediction of death in hemodialysis patients using support vector machine, neural network, logistic regression and decision tree.
Journal of preventive medicine and hygiene
Apr 29, 2021
OBJECTIVES: Chronic kidney disease (CKD) is one of the main causes of morbidity and mortality worldwide. Detecting survival modifiable factors could help in prioritizing the clinical care and offers a treatment decision-making for hemodialysis patien...
Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening.
IEEE journal of translational engineering in health and medicine
Apr 15, 2021
OBJECTIVE: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity and mortality rates in CKD patients, particularly in less deve...
Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach.
Scientific reports
Apr 14, 2021
Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healt...
Stay Ahead of Medical AI
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 31032
- Neural Networks, Computer 29717
- Algorithms 26831
- Deep Learning 26345
- Artificial Intelligence 24290
- Robotics 13311
- Image Processing, Computer-Assisted 9521
- Retrospective Studies 9110
- Magnetic Resonance Imaging 6181
- Reproducibility of Results 5592
- Tomography, X-Ray Computed 4770
- Support Vector Machine 4686
- Computational Biology 4236
- Brain 4050
- Computer Simulation 3881
Recent Journals
- Scientific reports 5940
- Sensors (Basel, Switzerland) 4794
- PloS one 4015
- Neural networks : the official journal of the International Neural Network Society 2929
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1854
- 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 1130
- Journal of chemical information and modeling 998
- Nature communications 943
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 826