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KTransNet: A Hybrid Transformer-CNN Framework For Early-Stage Chronic Kidney Disease Detection Using Multi-Modal Renal Imaging by International Journal of Innovative Science and Research Technology is a document available to read on EtoBox.
What is KTransNet: A Hybrid Transformer-CNN Framework For Early-Stage Chronic Kidney Disease Detection Using Multi-Modal Renal Imaging about?
The document presents KTransNet, a hybrid deep learning model combining Transformer encoders and CNN layers for early-stage Chronic Kidney Disease (CKD) detection using multi-modal renal imaging. The model achieved a mean accuracy of 96.3% and outperformed existing methods, demonstrating its potential as a clinical tool for automated CKD diagnosis. KTransNet utilizes a patch-based token embedding strategy and integrates a YOLOv8 detection head for effective feature extraction and lesion localization.
- Author
- International Journal of Innovative Science and Research Technology
- Language
- EN