Reconstructing and analyzing the invariances of low-dose CT image denoising networks.

Background: Deep learning-based methods led to significant advancements in many areas of medical imaging, most of which are concerned with the reduction of artifacts caused by motion, scatter, or noise. However, with most neural networks being black boxes, they remain notoriously difficult to interpret, hindering their clinical implementation. In particular, it has been shown that networks exhibit invariances w.

Peak amplitude of the normalized power spectrum of the electromyogram of the uterus in the low frequency band is an effective predictor of premature birth.

The current trends in the development of methods for non-invasive prediction of premature birth based on the electromyogram of the uterus, i.e., electrohysterogram (EHG), suggest an ever-increasing use of large number of features, complex models, and deep learning approaches.

Professional Values and Mental Health Tribunals: How Healthcare Professionals' and Lawyers' Views Are Shaped by Values, and How This Might Impede Reform.

Most countries that provide for compulsory treatment for mental illness have a system by which this treatment is subject to independent legal oversight. Many countries use a special type of legal body for this purpose, called a mental health tribunal. Mental health tribunals have been subject to criticism from the points of view of both legal professionals and mental healthcare practitioners.

Combining Critical Ethnography and Critical Discourse Analysis in Mental Health Nursing Research.

Background: It is uncommon to combine critical ethnography with critical discourse analysis (CDA) in health research, yet this combination has promise for managing challenges inherent in critical mental health nursing research.

Objectives: This article describes a methodologically innovative way to address issues that arise in the context of critical mental health nursing research.

Methods: This article draws on two studies that each employed a combination of critical ethnography and CDA in the context of mental health nursing research, discussing the challenges and implications of this approach.

Next-generation sequencing and comprehensive data reassessment in 263 adult patients with neuromuscular disorders: insights into the gray zone of molecular diagnoses.

Background: Neuromuscular disorders (NMDs) are heterogeneous conditions with a considerable fraction attributed to monogenic defects. Despite the advancements in genomic medicine, many patients remain without a diagnosis. Here, we investigate whether a comprehensive reassessment strategy improves the diagnostic outcomes.