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https://www.selleckchem.com/products/loxo-292.html The study demonstrated that CapsNet achieved the best discriminative performance (accuracy 81.3%, specificity 80.7%, sensitivity 82.2%) although its area under the curve was just marginally better than that of the optimal random forest (RF) based radiomics model. Not surprisingly, the performance of the CNN was only comparable to the other radiomics models. This study demonstrated that CapsNet is a viable potential framework for discriminating the subtypes of NSCLC, and its use could be extended to the recognition of other diseases especially in limited single-center datasets. This study demonstrated that CapsNet is a viable potential framework for discriminating the subtypes of NSCLC, and its use could be extended to the recognition of other diseases especially in limited single-center datasets. 3D motion-sensitized driven-equilibrium prepared rapid gradient echo (MERGE) can characterize carotid atherosclerotic plaque morphology and composition. The present study aimed to evaluate its performance by comparing it with reference images and assessing the inter-reader agreement. Eighty-four patients were prospectively recruited and scanned with 3D MERGE. Two trained magnetic resonance imaging (MRI) readers measured and calculated the maximum wall thickness (WT), maximum vessel diameter, total vessel area, lumen area, wall area, normalized wall index, plaque volume, intraplaque hemorrhage (IPH) volume, and calcification volume independently. IPH, calcification, mixed calcification, and ulceration were identified. The intraclass correlation coefficient (ICC) with 95% confidence interval (CI) was used to assess the inter-reader agreement. MERGE performance was assessed in terms of sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihoatherosclerotic plaques. Therefore, MERGE can be a promising imaging approach in atherosclerotic-vulnerable plaque. To ev

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