A patient developed a right pleural effusion soon after starting a program of continuous ambulatory peritoneal dialysis. The etiology of the effusion was unclear. 99mTc-labelled macroaggregated albumin was administered intrapentoneally, followed by 2 liters of dialysate. Trans-diaphragmatic leakage was clearly demonstrated, and confirmed by high count rates of pleural fluid with negligible blood count. This method can safely be used to demonstrate trans-diaphragmatic fluid leakage in peritoneal dialysis patients.
In the past few decades, skin diseases have been a hazardous issue because of more sophisticated and high-cost treatments. Identifying skin disease is still a challenging task for dermatologists. In reference to severe diseases like Melanoma, therapy in the initial stages is very important and effective to avoid skin cancer. This paper proposes an effective approach by using Vision Transformers (ViT) to detect Melanoma, which gives the accuracy of 99% on the test images. Authors considered the dataset, which is publicly available on Kaggle that comprises 1000 images and did the comprehensive study to get better results using ViT. The obtained results are compared with other state-of-the-art algorithms (VGG-19 and Inception-V3) to analyze the distinction between the proposed approach and other Convolutional Neural Network (CNN) Models.
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