This study investigated whether using an inertial measurement unit (IMU) can identify different walking conditions, including level walking (LW), descent (DC) and ascent (AC) slope walking as well as downstairs (DS) and upstairs (US) walking. Thirty ...
BACKGROUND: Poor quality primary health care is a major issue in China, particularly in blindness prevention. Artificial intelligence (AI) could provide early screening and accurate auxiliary diagnosis to improve primary care services and reduce unne...
Predicting the onset of psychosis in individuals at-risk is based on robust prognostic model building methods including a priori clinical knowledge (also termed clinical-learning) to preselect predictors or machine-learning methods to select predicto...
Machine learning techniques combined with wearable electronics can deliver accurate short-term blood glucose level prediction models. These models can learn personalized glucose-insulin dynamics based on the sensor data collected by monitoring severa...
The black sheep effect (BSE) describes the evaluative upgrading of norm-compliant group members (ingroup bias), and evaluative downgrading of deviant (norm-violating) group members, relative to similar outgroup members. While the BSE has been demonst...
BACKGROUND: Rapid, preoperative identification of patients with the highest risk for medical complications is necessary to ensure that limited infrastructure and human resources are directed towards those most likely to benefit. Existing risk scores ...
Australasian physical & engineering sciences in medicine
Oct 15, 2019
Living conditions of patients with refractory epilepsy will be significantly improved by a successful prediction of epileptic seizures. A proper warning impending seizure system should be resulted not only in high accuracy and low false positive alar...
BACKGROUND: Diabetes Mellitus is an increasingly prevalent chronic disease characterized by the body's inability to metabolize glucose. The objective of this study was to build an effective predictive model with high sensitivity and selectivity to be...
International journal of sports physiology and performance
Oct 14, 2019
PURPOSE: To use an artificial neural network (ANN) to model the effect of 15 weeks of resistance training on changes in countermovement jump (CMJ) performance in male track-and-field athletes.
There is significant interest in the development and application of deep neural networks (DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their classical counterparts in a variety of neuroimaging applications, yet there...
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