Development and external validation of a mixed-effects deep learning model to diagnose COVID-19 from CT imaging.

Background: The automatic analysis of medical images has the potential improve diagnostic accuracy while reducing the strain on clinicians. Current methods analyzing 3D-like imaging data, such as computerized tomography imaging, often treat each image slice as individual slices. This may not be able to appropriately model the relationship between slices.

Bilateral adaptive graph convolutional network on CT based Covid-19 diagnosis with uncertainty-aware consensus-assisted multiple instance learning.

Coronavirus disease (COVID-19) has caused a worldwide pandemic, putting millions of people's health and lives in jeopardy. Detecting infected patients early on chest computed tomography (CT) is critical in combating COVID-19. Harnessing uncertainty-aware consensus-assisted multiple instance learning (UC-MIL), we propose to diagnose COVID-19 using a new bilateral adaptive graph-based (BA-GCN) model that can use both 2D and 3D discriminative information in 3D CT volumes with arbitrary number of slices.

Quasiclassical trajectory study of H+SiH4 reactions in full-dimensionality reveals atomic-level mechanisms.

This work elucidates new atomic-level mechanisms that may be common in a range of chemical reactions, and our findings are important for the understanding of the nature of polyatomic abstraction and exchange reactions. A global 12-dimensional ab initio potential energy surface (PES), which describes both H+SiH(4) abstraction and exchange reactions is constructed, based on the modified Shepard interpolation method and UCCSD(T)/cc-pVQZ energy calculations at 4,015 geometries. This PES has a classical barrier height of 5.

Quasiclassical trajectory study of the SiH(4)+H-->SiH(3)+H(2) reaction on a global ab initio potential energy surface.

The SiH(4)+H-->SiH(3)+H(2) reaction has been investigated by the quasiclassical trajectory (QCT) method on a recent global ab initio potential energy surface [M. Wang et al., J.

A global 12-dimensional ab initio potential energy surface and dynamical studies for the SiH4+H-->SiH3+H2 reaction.

A global 12-dimensional ab initio interpolated potential energy surface (PES) for the SiH(4)+H-->SiH(3)+H(2) reaction is presented. The ab initio calculations are based on the unrestricted quadratic configuration interaction treatment with all single and double excitations together with the cc-pVTZ basis set, and the modified Shepard interpolation method of Collins and co-workers [K. C.