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Nephromind - Detection ,classification and segmentation of chronic kidney disease

  • Unique Paper ID: 179979
  • Volume: 11
  • Issue: 12
  • PageNo: 9113-9122
  • Abstract:
  • Kidney disease is a serious global health threat that needs to be detected early and classified accurately for proper management. NephroMind is a deep-learning integrated system that is intended to automatically recognize, classify, and segment kidney issues based on medical imaging. Advanced CNNs and transformer-based models are employed in the technique to extract salient features from renal ultrasonography and MRI scans. With the integration of multiple classifiers, a hybrid ensemble learning scheme enhances diagnostic accuracy and robustness. Utilizing U-Net and attention techniques for detecting trouble areas, the segmentation module enhances interpretability. The reliability of the system across a broad spectrum of situations is guaranteed through rigorous testing on benchmark datasets. Feature selection is optimized using Principal Component Analysis (PCA) to maintain diagnostic accuracy while minimizing processing load. NephroMind outperforms current models when compared on accuracy, recall, and F1 score. This research contributes to the development of AI supported nephrology by presenting an efficient, scalable, and explainable approach for kidney disease detection.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 12
  • PageNo: 9113-9122

Nephromind - Detection ,classification and segmentation of chronic kidney disease

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