Artificial intelligence models using F-wave responses predict amyotrophic lateral sclerosis.

Nerve conduction F-wave studies contain critical information about subclinical motor dysfunction which may be used to diagnose patients with amyotrophic lateral sclerosis (ALS). However, F-wave responses are highly variable in morphology, making waveform interpretation challenging. Artificial Intelligence techniques can extract time-frequency features to provide new insights into ALS diagnosis and prognosis.

Renewable energy transition in Europe in the context of renewable energy transition processes in the world. A review.

Both the global and European energy sectors have been undergoing a deep transition for several years, associated with a reduction in the overall share of conventional coal-based energy in favor of new technologies, especially energy from renewable sources (RES). This transition is moving from centralized production towards distributed technologies and from providing only energy to end users towards combining innovative products and services with it. Electricity consumers are becoming prosumers connected to the grid and generating an increasing amount of energy.

A validation study demonstrating portable motion capture cameras accurately characterize gait metrics when compared to a pressure-sensitive walkway.

Digital quantification of gait can be used to measure aging- and disease-related decline in mobility. Gait performance also predicts prognosis, disease progression, and response to therapies. Most gait analysis systems require large amounts of space, resources, and expertise to implement and are not widely accessible.

Soft tissue sarcomas of the head and neck region: clinical and histopathological study of 39 patients.

<b>Introduction:</b> Soft tissue sarcomas (STS) constitute about 1-2% of all malignant tumors, with approximately 10% of them located in the head and neck region.<b>Aim:</b> The aim of this study was the assessment of treatment efficiency in head and neck STS of adult patients of the ENT Department of Medical University of Silesia, treated surgically in the period 1980-2023.<b>Materials and methods:</b> Retrospective analysis of 39 patients with the diagnosis of head and neck STS.