Burns : journal of the International Society for Burn Injuries
25931158
INTRODUCTION: Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational faci...
BACKGROUND: Electronic medical record (EMR) systems have become widely used throughout the world to improve the quality of healthcare and the efficiency of hospital services. A bilingual medical lexicon of Chinese and English is needed to meet the de...
BACKGROUND: NHS England's Five Year Forward View (NHS England, Five Year Forward View, 2014) formally introduced a strategy for new models of care driven by simultaneous pressures to contain costs, improve care and deliver services closer to home thr...
This paper provides evidence on the usefulness of very high spatial resolution (VHR) imagery in gathering socioeconomic information in urban settlements. We use land cover, spectral, structure and texture features extracted from a Google Earth image ...
INTRODUCTION: Interventions using robot-assisted therapy may be beneficial for the social skills development of children with autism spectrum disorder (ASD); however, randomised controlled trials (RCTs) are lacking. The present research aims to asses...
The availability alongside growing awareness of medicine has led to increased self-treatment of minor ailments. Self-medication is where one 'self' diagnoses and prescribes over the counter medicines for treatment. The self-care movement has importan...
This work was part of a National Institute for Health Research participatory action research and practice development study, which focused on the use of a therapeutic, robotic baby seal (PARO, for personal assistive robot) in everyday practice in a s...
In this paper, we propose a structural framework for population-based cancer epidemiology and evaluate the performance of double-robust estimators for a binary exposure in cancer mortality. We conduct numerical analyses to study the bias and efficien...
BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of ca...
BACKGROUND: The relationship between allergic sensitisation and asthma is complex; the data about the strength of this association are conflicting. We propose that the discrepancies arise in part because allergic sensitisation may not be a single ent...