AIMC Topic: Kidney Diseases
Clear Filters Showing 81 to 90 of 100 articles
MACHINE LEARNING AND SHOCK INDICES-DERIVED SCORE FOR PREDICTING CONTRAST-INDUCED NEPHROPATHY IN ACUTE CORONARY SYNDROME PATIENTS.
Shock (Augusta, Ga.)
Jul 1, 2025
Background: Contrast-induced nephropathy (CIN) is a serious complication following acute coronary syndrome (ACS), leading to increased morbidity and mortality. Machine learning (ML), combined with parameters such as shock indices, can potentially imp...
An explainable adaptive channel weighting-based deep convolutional neural network for classifying renal disorders in computed tomography images.
Computers in biology and medicine
Jun 1, 2025
Renal disorders are a significant public health concern and a cause of mortality related to renal failure. Manual diagnosis is subjective, labor-intensive, and depends on the expertise of nephrologists in renal anatomy. To improve workflow efficiency...
Multi-level feature fusion network for kidney disease detection.
Computers in biology and medicine
Jun 1, 2025
Kidney irregularities pose a significant public health challenge, often leading to severe complications, yet the limited availability of nephrologists makes early detection costly and time-consuming. To address this issue, we propose a deep learning ...
Ethical considerations on the use of big data and artificial intelligence in kidney research from the ERA ethics committee.
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Feb 28, 2025
In the current paper, we will focus on requirements to ensure big data can advance the outcomes of our patients suffering from kidney disease. The associated ethical question is whether and how we as a nephrology community can and should encourage th...
Integrated multi-omics with machine learning to uncover the intricacies of kidney disease.
Briefings in bioinformatics
Jul 25, 2024
The development of omics technologies has driven a profound expansion in the scale of biological data and the increased complexity in internal dimensions, prompting the utilization of machine learning (ML) as a powerful toolkit for extracting knowled...
LLM-based kidney disease diagnostic framework for Pathologists.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Large language models revolutionize the recent paradigm in the medical field and its contributing to various applications, diversified from clinical decision support to information extraction and summarization. The substantial linguistic understandin...
Prediction of Vancomycin-Associated Nephrotoxicity Based on the Area under the Concentration-Time Curve of Vancomycin: A Machine Learning Analysis.
Biological & pharmaceutical bulletin
Jan 1, 2024
Several machine learning models have been proposed to predict vancomycin (VCM)-associated nephrotoxicity; however, they have notable limitations. Specifically, they do not use the area under the concentration-time curve (AUC) as recommended in the la...
[Application progress of machine learning in kidney disease].
Zhonghua wei zhong bing ji jiu yi xue
Dec 1, 2023
Kidney disease affects a large number of people around the world, imposing a significant burden to people's health and life. If early prediction, rapid diagnosis and prognosis prediction of kidney disease can be carried out, the health of patients wi...
A Deep Learning-Based Approach for Glomeruli Instance Segmentation from Multistained Renal Biopsy Pathologic Images.
The American journal of pathology
Aug 1, 2021
Glomeruli instance segmentation from pathologic images is a fundamental step in the automatic analysis of renal biopsies. Glomerular histologic manifestations vary widely among diseases and cases, and several special staining methods are necessary fo...
Artificial intelligence with kidney disease: A scoping review with bibliometric analysis, PRISMA-ScR.
Medicine
Apr 9, 2021
BACKGROUND: Artificial intelligence (AI) has had a significant impact on our lives and plays many roles in various fields. By analyzing the past 30 years of AI trends in the field of nephrology, using a bibliography, we wanted to know the areas of in...
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 32006
- Neural Networks, Computer 30221
- Algorithms 27397
- Deep Learning 26901
- Artificial Intelligence 24835
- Robotics 13387
- Image Processing, Computer-Assisted 9735
- Retrospective Studies 9342
- Magnetic Resonance Imaging 6346
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4865
- Support Vector Machine 4769
- Computational Biology 4332
- Brain 4129
- Computer Simulation 3935
Recent Journals
- Scientific reports 6775
- Sensors (Basel, Switzerland) 4794
- PloS one 4200
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- 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 1378
- IEEE journal of biomedical and health informatics 1172
- Journal of chemical information and modeling 1064
- Nature communications 1044
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 873
- Journal of medical Internet research 861
- Briefings in bioinformatics 853