OBJECTIVE: Self-anamnesis is a procedure in which a patient answers questions about the personal medical history without interacting directly with a doctor or medical assistant. If collected digitally, the anamnesis data can be shared among the healt...
Disability and rehabilitation. Assistive technology
Mar 11, 2019
Upper limb prostheses are part of a rapidly changing market place. Despite development in device design, surveys report low levels of uptake and dissatisfaction with current prosthetic design. In this study, we present the results of a survey conduc...
Literature Based Discovery (LBD) refers to the problem of inferring new and interesting knowledge by logically connecting independent fragments of information units through explicit or implicit means. This area of research, which incorporates techniq...
INTRODUCTION: Using machine learning techniques, we developed a brief questionnaire to aid neurologists and neuropsychologists in the screening of mild cognitive impairment (MCI) and dementia.
: This study set out to empirically identify joint health trajectories in individuals of advanced age. Predictors of subgroup allocation were investigated to identify the impact of psychological characteristics, stress, and socio-demographic variable...
Effective wildlife management relies on the accurate and precise detection of individual animals. These can be challenging data to collect for many cryptic species, particularly those that live in complex structural environments. This study introduce...
BACKGROUND: The combination of growth hormone (GH) and aromatase inhibitors (AI) improves linear growth in severely short adolescent boys; however, the effects of this intervention on quality of life (QoL) are unknown. This study assesses whether GH,...
INTRODUCTION: This study aims to obtain data on the prevalence and incidence of structural heart disease in a population setting and, to analyse and present those data on the application of spatial and machine learning methods that, although known to...
Neural networks are powerful tools used widely for building cancer prediction models from microarray data. We review the most recently proposed models to highlight the roles of neural networks in predicting cancer from gene expression data. We identi...
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