AIMC Topic: Young Adult

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Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

Food research international (Ottawa, Ont.)
In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by do...

Pattern of improvement in upper limb pointing task kinematics after a 3-month training program with robotic assistance in stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: When exploring changes in upper limb kinematics and motor impairment associated with motor recovery in subacute post stroke during intensive therapies involving robot-assisted training, it is not known whether trained joints improve befor...

Use of automated learning techniques for predicting mandibular morphology in skeletal class I, II and III.

Forensic science international
BACKGROUND: The prediction of the mandibular bone morphology in facial reconstruction for forensic purposes is usually performed considering a straight profile corresponding to skeletal class I, with application of linear and parametric analysis whic...

Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.

International journal of medical informatics
BACKGROUND: Mortality prediction of hospitalized patients is an important problem. Over the past few decades, several severity scoring systems and machine learning mortality prediction models have been developed for predicting hospital mortality. By ...

The effectiveness of robotic training depends on motor task characteristics.

Experimental brain research
Previous research suggests that the effectiveness of robotic training depends on the motor task to be learned. However, it is still an open question which specific task's characteristics influence the efficacy of error-modulating training strategies....

Tele-Manipulation with Two Asymmetric Slaves: Two Operators Perform Better Than One.

IEEE transactions on haptics
Certain tele-manipulation tasks require manipulation by two asymmetric slaves, for example, a crane for hoisting and a dexterous robotic arm for fine manipulation. It is unclear how to best design human-in-the-loop control over two asymmetric slaves....

Using Temporal Sensitivity to Predict Performance Under Latency in Teleoperation.

Human factors
Objective This article establishes a relationship between temporal sensitivity and task performance under one-way latency between input and response. Background As the latency between human input and telerobot response increases, performance (e.g., s...

Real-Time Non-Invasive Detection and Classification of Diabetes Using Modified Convolution Neural Network.

IEEE journal of biomedical and health informatics
Non-invasive diabetes prediction has been gaining prominence over the last decade. Among many human serums evaluated, human breath emerges as a promising option with acetone levels in breath exhibiting a good correlation to blood glucose levels. Such...

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

Environmental health : a global access science source
BACKGROUND: There is growing concern of health effects of exposure to pollutant mixtures. We initially proposed an Environmental Risk Score (ERS) as a summary measure to examine the risk of exposure to multi-pollutants in epidemiologic research consi...