Asynchronous Video Directly Observed Therapy to Monitor Short-Course Latent Tuberculosis Infection Treatment: Results of a Randomized Controlled Trial.

Background: Observing medication ingestion through self-recorded videos (video directly observed therapy [VDOT]) has been shown to be a cost-effective alternative to in-person directly observed therapy (DOT) for monitoring adherence to treatment for tuberculosis disease. VDOT could be a useful tool to monitor short-course latent tuberculosis infection (LTBI) treatment.

Methods: We conducted a prospective randomized controlled trial comparing VDOT (intervention) and clinic-based DOT (control) among patients newly diagnosed with LTBI who agreed to a once-weekly 3-month treatment regimen of isoniazid and rifapentine.

Investigation of an efficient multi-modal convolutional neural network for multiple sclerosis lesion detection.

In this study, an automated 2D machine learning approach for fast and precise segmentation of MS lesions from multi-modal magnetic resonance images (mmMRI) is presented. The method is based on an U-Net like convolutional neural network (CNN) for automated 2D slice-based-segmentation of brain MRI volumes. The individual modalities are encoded in separate downsampling branches without weight sharing, to leverage the specific features.

Application of A U-Net for Map-like Segmentation and Classification of Discontinuous Fibrosis Distribution in Gd-EOB-DTPA-Enhanced Liver MRI.

We aimed to evaluate whether U-shaped convolutional neuronal networks can be used to segment liver parenchyma and indicate the degree of liver fibrosis/cirrhosis at the voxel level using contrast-enhanced magnetic resonance imaging. This retrospective study included 112 examinations with histologically determined liver fibrosis/cirrhosis grade (Ishak score) as the ground truth. The T1-weighted volume-interpolated breath-hold examination sequences of native, arterial, late arterial, portal venous, and hepatobiliary phases were semi-automatically segmented and co-registered.

Constraints on Cosmic Strings Using Data from the Third Advanced LIGO-Virgo Observing Run.

We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset. Search results are presented for gravitational waves produced by cosmic string loop features such as cusps, kinks, and, for the first time, kink-kink collisions. A template-based search for short-duration transient signals does not yield a detection.