July 2024
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8 Reads
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2 Citations
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Publications (1)
Citations (1)
... Their work highlighted CNNs' ability to capture complex patterns in medical images, which is essential for early detection of MS lesions. Langat et al. [13] advanced this concept further by integrating 6G-enabled Internet of Medical Things technology with DenseNets, showing significant improvements in diagnostic accuracy, particularly in cases of acute transverse myelitis. Langat et al. [14] focused on refining lesion segmentation using the MSAT algorithm and HDCARAN classifier, demonstrating enhanced precision in MRI analysis, while Ponce de Leon-Sanchez et al. [15] explored various DL architectures, including LSTM-CNN and GAN, to understand their applications across different neurological diseases. ...
- Citing Conference Paper
July 2024