A scoping review of cephalometric normative data in children.

Objective: Understanding the orofacial characteristics and growth patterns in children is essential for both orthodontics and research on children with orofacial abnormalities. However, a concise resource of normative data on the size and relative position of these structures in different populations is not available. Our objective was to aggregate normative data to assess the growth of the orofacial skeletal structures in children with a well-balanced face and normal occlusion.

Trip-Related Fall Risk Prediction Based on Gait Pattern in Healthy Older Adults: A Machine-Learning Approach.

Trip perturbations are proposed to be a leading cause of falls in older adults. To prevent trip-falls, trip-related fall risk should be assessed and subsequent task-specific interventions improving recovery skills from forward balance loss should be provided to the individuals at risk of trip-fall. Therefore, this study aimed to develop trip-related fall risk prediction models from one's regular gait pattern using machine-learning approaches.