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References from A robust privacy-preserving federated framework for kidney CT image classification using transfer learning models. Local targets link to admitted publications; unresolved targets remain external evidence.
A robust EfficientNetV2-S classifier for predicting acute lymphoblastic leukemia based on cross validation
10.3390/sym17010024 · 2024 · External reference
Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor
10.1186/s12880-024-01261-0 · 2024 · External reference
Federated learning approach for breast cancer detection based on dcnn
10.1109/access.2024.3374650 · 2024 · External reference
“Classification of paediatric pneumonia using modified DenseNet-121 deep-learning model,”
10.1109/access.2024.3371151 · 2024 · External reference
“Federated learning with AutoAlbum for kidney disease detection: a privacy-preserving approach to medical image analysis,”
10.1109/access.2025.3602224 · 2025 · External reference
Exploring the capabilities of a lightweight CNN model in accurately identifying renal abnormalities: cysts, stones, and tumors, using LIME and SHAP
10.3390/app13053125 · 2023 · External reference
FedDL: personalized federated deep learning for enhanced detection and classification of diabetic retinopathy
10.7717/peerj-cs.2508 · 2024 · External reference
Automatic classification of kidney CT images with relief based novel hybrid deep model
10.7717/peerj-cs.1717 · 2023 · External reference
Risk-directed management of chronic kidney disease
10.1038/s41581-025-00931-8 · 2025 · External reference
Federated learning: a new frontier in the exploration of multi-institutional medical imaging data
10.1016/j.cmpb.2026.109454 · 2026 · External reference
10.1007/978-3-662-04722-4
10.1007/978-3-662-04722-4 · 2002 · External reference
“Classification of kidney abnormalities in ct images using deep learning,”
2025 · External reference
Integrating neural networks with advanced optimization techniques for accurate kidney disease diagnosis
10.1038/s41598-024-71410-6 · 2024 · External reference
Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016-40 for 195 countries and territories
10.1016/s0140-6736(18)31694-5 · 2018 · External reference
Feature extraction based on local histogram with unequal bins and a recurrent neural network for the diagnosis of kidney diseases from CT images
10.3390/bioengineering11030220 · 2024 · External reference
Unresolved reference
2009 · External reference
“Deep residual learning for image recognition,”
2016 · External reference
Designing efficient anomaly detection systems using deep learning techniques
10.1108/ijpcc-08-2024-0262 · 2026 · External reference
A new lung cancer detection method based on the chest CT images using federated learning and blockchain systems
10.1016/j.artmed.2023.102572 · 2023 · External reference
The KiTS19 challenge data: 300 kidney tumor cases with clinical context, ct semantic segmentations, and surgical outcomes
10.48550/arxiv.1904.00445 · 2019 · External reference
Transfer learning with fine-tuned deep CNN ResNet50 model for classifying COVID-19 from chest X-ray images
10.1016/j.imu.2022.100916 · 2022 · External reference
“Densely connected convolutional networks,”
2017 · External reference
Fairness and accuracy in horizontal federated learning
10.1016/j.ins.2021.12.102 · 2022 · External reference
Melanoma image classification based on MobileNetv2 network
10.1016/j.procs.2021.12.132 · 2022 · External reference
Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from ct-radiography
10.1038/s41598-022-15634-4 · 2022 · External reference
A single number for advocacy and communication–worldwide more than 850 million individuals have kidney diseases
10.1016/j.kint.2019.07.012 · 2019 · External reference
The state of nephrology in South Asia
10.1016/j.kint.2018.09.001 · 2019 · External reference
Chronic kidney disease
10.1016/s0140-6736(21)00519-5 · 2021 · External reference
Privacy-preserving federated learning and uncertainty quantification in medical imaging
10.1148/ryai.240637 · 2025 · External reference
Epidemiology of chronic kidney disease: an update 2022
10.1016/j.kisu.2021.11.003 · 2022 · External reference
A comprehensive study of deep learning methods for kidney tumor, cyst, and stone diagnostics and detection using CT images
10.1007/s11831-024-10112-8 · 2024 · External reference
Deep learning
10.1038/nature14539 · 2015 · External reference
Reviewing federated learning aggregation algorithms; strategies, contributions, limitations and future perspectives
10.3390/electronics12102287 · 2023 · External reference
Multi-model deep learning approach for the classification of kidney diseases using medical images
10.1016/j.imu.2025.101663 · 2025 · External reference
Multi-class kidney abnormalities detecting novel system through computed tomography
10.1109/access.2024.3351181 · 2024 · External reference
Fine-tuned deep learning models for early detection and classification of kidney conditions in CT imaging
10.1038/s41598-025-94905-2 · 2025 · External reference
Lung-AttNet: an attention mechanism-based CNN architecture for lung cancer detection with federated learning
10.1109/access.2025.3554744 · 2025 · External reference
“MobileNetV2: inverted residuals and linear bottlenecks,”
2018 · External reference
Digital twin of renal system with CT-radiography for the early diagnosis of chronic kidney diseases
10.1016/j.bspc.2023.105632 · 2024 · External reference
Development and external validation of a predictive model for lung metastases in kidney cancer based on clinical and laboratory features
10.1007/s10238-025-01839-0 · 2025 · External reference
“Federated learning approaches to diverse machine learning model: a review,”
2023 · External reference
Clinical course of lung cancer in patients with chronic kidney disease
10.1016/j.chest.2016.08.823 · 2016 · External reference
A systematic review on federated learning in medical image analysis
10.1109/access.2023.3260027 · 2023 · External reference
Enhancing medical image classification via federated learning and pre-trained model
10.1016/j.eij.2024.100530 · 2024 · External reference
An adaptive eroded deep convolutional neural network for brain image segmentation and classification using inception resnetv2
10.1016/j.bspc.2022.103863 · 2022 · External reference
“Inception-v4, inception-ResNet and the impact of residual connections on learning,”
10.1609/aaai.v31i1.11231 · 2017 · External reference
“EfficientNetV2: smaller models and faster training,”
2021 · External reference
A transfer learning approach to breast cancer classification in a federated learning framework
10.1109/access.2023.3257562 · 2023 · External reference
Practical approach to detection and management of chronic kidney disease for the primary care clinician
10.1016/j.amjmed.2015.08.025 · 2016 · External reference
10.1186/s40537-016-0043-6 · 2016 · Admitted local publication