Neck and Shoulder Pain with Scapular Dyskinesis in Computer Office Workers.

Computer office workers spend long periods in front of a computer, and neck and shoulder pain are common. Scapular dyskinesis (SD) is associated with neck and shoulder pain. However, SD in computer office workers has not been elucidated.

GenHPF: General Healthcare Predictive Framework for Multi-task Multi-source Learning.

Despite the remarkable progress in the development of predictive models for healthcare, applying these algorithms on a large scale has been challenging. Algorithms trained on a particular task, based on specific data formats available in a set of medical records, tend to not generalize well to other tasks or databases in which the data fields may differ. To address this challenge, we propose General Healthcare Predictive Framework (GenHPF), which is applicable to any EHR with minimal preprocessing for multiple prediction tasks.

MaDeNet: Disentangling Individuality of EEG Signals through Feature Space Mapping and Detachment.

The cross-subject variability, or individuality, of electroencephalography (EEG) signals often has been an obstacle to extracting target-related information from EEG signals for classification of subjects' perceptual states. In this paper, we propose a deep learning-based EEG classification approach, which learns feature space mapping and performs individuality detachment to reduce subject-related information from EEG signals and maximize classification performance. Our experiment on EEG-based video classification shows that our method significantly improves the classification accuracy.

Emotional EEG classification using connectivity features and convolutional neural networks.

Convolutional neural networks (CNNs) are widely used to recognize the user's state through electroencephalography (EEG) signals. In the previous studies, the EEG signals are usually fed into the CNNs in the form of high-dimensional raw data. However, this approach makes it difficult to exploit the brain connectivity information that can be effective in describing the functional brain network and estimating the perceptual state of the user.