Data-driven machine learning (ML) has emerged as a promising approach for building
accurate and robust statistical models from medical data, which is collected in huge volumes by …

… concentrations were incubated for at least 4 h to reach equilibrium unfolding prior to experiments.
… concentrations of GdmCl were incubated for at least 5 h to reach equilibrium unfolding. …

The structures and catalytic properties of zeolites have been intensively investigated as
prototypes of acidic industrial catalysts. 1-12 Zeolites were first introduced as catalysts for large-…

… H. Roth and M. Gao contributed equally … GoogLeNet-TL-H yields results similar to
AlexNet-TL-H's for the mediastinal LN detection, and slightly outperforms Alex-Net-…

Fully Convolutional Neural Networks (FCNNs) with contracting and expanding paths have
shown prominence for the majority of medical image segmentation applications since the past …

Semantic segmentation of brain tumors is a fundamental medical image analysis task involving
multiple MRI imaging modalities that can assist clinicians in diagnosing the patient and …

Vision Transformers (ViT) s have shown great performance in self-supervised learning of
global and local representations that can be transferred to downstream applications. Inspired …

Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19
associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of …

Automatic organ segmentation is an important yet challenging problem for medical image
analysis. The pancreas is an abdominal organ with very high anatomical variability. This …

Herein, we report half-peak potentials for over 180 organic substrates obtained via cyclic
voltammetry. These values are of great use in assessing the thermodynamics of an electron-…