Assessment of frailty in elderly patients attending a multidisciplinary wound care centre: a cohort study.

Background: The incidence of frailty and non-healing wounds increases with patients' age. Knowledge of the relationship between frailty and wound healing progress is greatly lacking.

Methods: The aim of this study is to characterize the degree of frailty in elderly patients attending a multidisciplinary wound care centres (MWCC).

Convolutional Neural Network for Skin Lesion Classification: Understanding the Fundamentals Through Hands-On Learning.

Deep learning architectures for the classification of images have shown outstanding results in a variety of disciplines, including dermatology. The expectations generated by deep learning for, e.g.

A toolkit for the quantitative evaluation of chronic wounds evolution for early detection of non-healing wounds.

Background: Chronic wounds resulting from a number of conditions do not heal properly and can pose serious health problems. Beyond clinician visual inspection, an objective evaluation of the wound is required to assess wound evolution and the effectiveness of therapies.

Aim: Our objective is to provide a methodology for the analysis of wound area vs.

Research Techniques Made Simple: Deep Learning for the Classification of Dermatological Images.

Deep learning is a branch of artificial intelligence that uses computational networks inspired by the human brain to extract patterns from raw data. Development and application of deep learning methods for image analysis, including classification, segmentation, and restoration, have accelerated in the last decade. These tools have been progressively incorporated into several research fields, opening new avenues in the analysis of biomedical imaging.

Bayesian analysis of data from segmented super-resolution images for quantifying protein clustering.

Super-resolution imaging techniques have largely improved our capabilities to visualize nanometric structures in biological systems. Their application further permits the quantitation relevant parameters to determine the molecular organization and stoichiometry in cells. However, the inherently stochastic nature of fluorescence emission and labeling strategies imposes the use of dedicated methods to accurately estimate these parameters.