AIMC Topic: Male

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Prediction of activity type in preschool children using machine learning techniques.

Journal of science and medicine in sport
OBJECTIVES: Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting ...

Modified robotic-assisted thyroidectomy: an initial experience with the retroauricular approach.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: New approaches for robotic-assisted thyroidectomy, including the retroauricular approach, were recently described. We have modified the established surgical approach for retroauricular robotic thyroidectomy. Herein, we report o...

Predicting outcomes in patients with perforated gastroduodenal ulcers: artificial neural network modelling indicates a highly complex disease.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: Mortality prediction models for patients with perforated peptic ulcer (PPU) have not yielded consistent or highly accurate results. Given the complex nature of this disease, which has many non-linear associations with outcomes, we explored a...

Design of multiple axis robotic platform for postural stability analysis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper presents the design and implementation of IsiMove, a new dynamic posturography platform. It allows the evaluation of the static and dynamic balance of a human placed on a force plate. IsiMove is a robotic platform open kinematic with four ...

Epileptic seizure prediction using relative spectral power features.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Prediction of epileptic seizures can improve the living conditions for refractory epilepsy patients. We aimed to improve sensitivity and specificity of prediction methods, and to reduce the number of false alarms.

Time-frequency modulation of ERD and EEG coherence in robot-assisted hand performance.

Brain topography
A better understanding of cortical modifications related to movement preparation and execution after robot-assisted training could aid in refining rehabilitation therapy protocols for stroke patients. Electroencephalography (EEG) modifications of cor...

Decoding objects of basic categories from electroencephalographic signals using wavelet transform and support vector machines.

Brain topography
Decoding and classification of objects through task-oriented electroencephalographic (EEG) signals are the most crucial goals of recent researches conducted mainly for brain-computer interface applications. In this study we aimed to classify single-t...

Identifying Neuroimaging Markers of Motor Disability in Acute Stroke by Machine Learning Techniques.

Cerebral cortex (New York, N.Y. : 1991)
Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms represent a multivariate decoding approach that may help to identify neuroimaging patterns associate...

Real-time prediction of disordered breathing events in people with obstructive sleep apnea.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Conventional therapies for obstructive sleep apnea (OSA) are effective but suffer from poor patient adherence and may not fully alleviate major OSA-associated cardiovascular risk factors or improve certain aspects of quality of life. Predict...