Efficient Training of Probabilistic Neural Networks for Survival Analysis.

Variational Inference (VI) is a commonly used technique for approximate Bayesian inference and uncertainty estimation in deep learning models, yet it comes at a computational cost, as it doubles the number of trainable parameters to represent uncertainty. This rapidly becomes challenging in high-dimensional settings and motivates the use of alternative techniques for inference, such as Monte Carlo Dropout (MCD) or Spectral-normalized Neural Gaussian Process (SNGP). However, such methods have seen little adoption in survival analysis, and VI remains the prevalent approach for training probabilistic neural networks.

An Evaluation of Commercial Pedometers for Monitoring Slow Walking Speed Populations.

Background: Pedometers are considered desirable devices for monitoring physical activity. Two population groups of interest include patients having undergone surgery in the lower extremities or who are otherwise weakened through disease, medical treatment, or surgery procedures, as well as the slow walking senior population. For these population groups, pedometers must be able to perform reliably and accurately at slow walking speeds.

Ambient assisted living healthcare frameworks, platforms, standards, and quality attributes.

Ambient Assisted Living (AAL) is an emerging multi-disciplinary field aiming at exploiting information and communication technologies in personal healthcare and telehealth systems for countering the effects of growing elderly population. AAL systems are developed for personalized, adaptive, and anticipatory requirements, necessitating high quality-of-service to achieve interoperability, usability, security, and accuracy. The aim of this paper is to provide a comprehensive review of the AAL field with a focus on healthcare frameworks, platforms, standards, and quality attributes.

Training brain retraction in a virtual reality environment.

A computer based virtual reality system is presented allowing the user to train skills related to brain retraction. The system is designed and the core training system implemented and tested. The initial test shows promising results.

Modelling of interaction between a spatula and a human brain.

This paper describes a method for surgery simulation, or more specifically a learning system of how to use a brain spatula. Improper use of brain spatulas can lead to brain tissue lesions such as tearing of brain tissue and ischemia. The idea is to provide surgeons with a tool which can teach them the correlation between deformation and applied force.