Nodule Detection and Generation on Chest X-Rays: NODE21 Challenge.

Pulmonary nodules may be an early manifestation of lung cancer, the leading cause of cancer-related deaths among both men and women. Numerous studies have established that deep learning methods can yield high-performance levels in the detection of lung nodules in chest X-rays. However, the lack of gold-standard public datasets slows down the progression of the research and prevents benchmarking of methods for this task.

Artificial Intelligence Applied to Chest X-ray: A Reliable Tool to Assess the Differential Diagnosis of Lung Pneumonia in the Emergency Department.

Background: Considering the large number of patients with pulmonary symptoms admitted to the emergency department daily, it is essential to diagnose them correctly. It is necessary to quickly solve the differential diagnosis between COVID-19 and typical bacterial pneumonia to address them with the best management possible. In this setting, an artificial intelligence (AI) system can help radiologists detect pneumonia more quickly.

Accelerated molecular dynamics simulation of thin-film growth with the bond-boost method.

We review the bond-boost method for accelerated molecular dynamics (MD) simulation and we demonstrate its application to kinetic phenomena relevant to thin-film growth. To illustrate various aspects of the method, three case studies are presented. We first illustrate aspects of the bond-boost method in studies of the diffusion of Cu atoms on Cu(001).

Multiple-time scale accelerated molecular dynamics: addressing the small-barrier problem.

We present a method for accelerated molecular-dynamics simulation in systems with rare-event dynamics that span a wide range of time scales. Using a variant of hyperdynamics, we detect, on the fly, groups of recurrent states connected by small energy barriers and we modify the potential-energy surface locally to consolidate them into large, coarse states. In this way, fast motion between recurrent states is treated within an equilibrium formalism and dynamics can be simulated over the longer time scale of the slow events.

Thermal desorption of large molecules from solid surfaces.

We use molecular-dynamics simulations and importance sampling to obtain transition-state-theory rate constants for thermal desorption of an n-alkane series from Au(111). We find that the binding of a large molecule to a solid surface involves different types of local minima. The preexponential factors increase with increasing chain length and can be substantially larger than typical estimates for small molecules.