Objectives: Abusive head trauma (AHT) is a leading cause of death in young children. Analyses of patient characteristics presenting to Emergency Medical Services (EMS) are often limited to structured data fields. Artificial Intelligence (AI) and Large Language Models (LLM) may identify rare presentations like AHT through factors not found in structured data.
View Article and Find Full Text PDFHuman visual attention allows prior knowledge or expectations to influence visual processing, allocating limited computational resources to only that part of the image that are likely to behaviourally important. Here, we present an image recognition system based on biological vision that guides attention to more informative locations within a larger parent image, using a sequence of saccade-like motions. We demonstrate that at the end of the saccade sequence the system has an improved classification ability compared to the convolutional neural network (CNN) that represents the feedforward part of the model.
View Article and Find Full Text PDFResearch Question: What are the experiences of users of period tracking apps in relation to which apps they use, their frequency of use, the type of data and their attitudes to period tracking apps?
Design: This was an observational mixed-methods study using an online survey designed using Qualtrics XM. The survey included 50 open-ended and multiple choice questions, but only specific questions were analysed in this study. The survey was promoted via social media for 22 days between 30 June and 21 July 2021.
Unlabelled: Limited work examining woman's appetite-regulatory response to exercise has been focused on the follicular phase (FP) of the menstrual cycle. This is an important limitation as estradiol (E) and progesterone (P) fluctuate across phases with greater concentrations in the luteal phase (LP).
Objective: To examine the appetite-regulatory response to vigorous-intensity continuous exercise (VICT) in the FP and LP.