An Artificial Neural Network for Nasogastric Tube Position Decision Support.

Purpose: To develop and validate a deep learning model for detection of nasogastric tube (NGT) malposition on chest radiographs and assess model impact as a clinical decision support tool for junior physicians to help determine whether feeding can be safely performed in patients (feed/do not feed).

Materials And Methods: A neural network ensemble was pretrained on 1 132 142 retrospectively collected (June 2007-August 2019) frontal chest radiographs and further fine-tuned on 7081 chest radiographs labeled by three radiologists. Clinical relevance was assessed on an independent set of 335 images.

Comparison between the Visual Analog Scale and the Numerical Rating Scale in the perception of esthetics and pain.

Background: Pain is an unpleasant, emotional, and sensorial experience. Esthetics and pain express perceptions or sensations that are subjective and personal, but non-consensual, between professionals and patients. The Visual Analog Scale (VAS) and the Numerical Rating Scale (NRS) are simple methods to evaluate such subjective phenomena.

Novel non-calcemic secosteroids that are produced by human epidermal keratinocytes protect against solar radiation.

CYP11A1 hydroxylates the side chain of vitamin D3 (D3) in a sequential fashion [D3→20S(OH)D3→20,23(OH)2D3→17,20,23(OH)3D3], in an alternative to the classical pathway of activation [D3→25(OH)D3→1,25(OH)2D3]. The products/intermediates of the pathway can be further modified by the action of CYP27B1. The CYP11A1-derived products are biologically active with functions determined by the lineage of the target cells.