Transactions on Neural Systems and Rehabilitation Engineering

Featured Articles
From Group-Level Statistics to Single-Subject Prediction: Machine Learning Detection of Concussion in Retired Athletes
Rober Boshra, Kiret Dhindsa, Omar Boursalie, Kyle I. Ruiter, Ranil Sonnadara, Reza Samavi, Thomas E. Doyle, James P. Reilly, John F. Connolly
         There has been increased effort to understand the neurophysiological effects of concussion aimed to move diagnosis and identification beyond current subjective behavioral assessments that suffer from poor sensitivity. Recent evidence suggests that event-related potentials (ERPs) measured with electroencephalography (EEG) are... Read more
Posted on 18 JUL 2019
Articles, Published Articles
Cardiac-DeepIED: Automatic Pixel-level Deep Segmentation for Cardiac Bi-ventricle Using Improved End-to-End Encoder-Decoder Network
Xiuquan Du, Susu Yin, Renjun Tang, Yanping Zhang, Shuo Li
     Abstract Accurate segmentation of cardiac bi-ventricle (CBV) from magnetic resonance (MR) images has a great significance to analyze and evaluate the function of the cardiovascular system. However, the complex structure of CBV image makes fully automatic segmentation as a well-known challenge.... Read more
Posted on 8 MAR 2019
Featured Articles
MfeCNN: Mixture Feature Embedding Convolutional Neural Network for Data Mapping
Dingcheng Li, Ming Huang, Xiaodi Li, Yaoping Ruan, Lixia Yao
Data mapping plays an important role in data integration and exchanges among institutions and organizations with different data standards. However, traditional rule-based approaches and machine learning methods fail to achieve satisfactory results for the data mapping problem. In this paper,... Read more
Posted on 6 AUG 2018
Featured Articles
PhosPred-RF: a novel sequence-based predictor for phosphorylation sites using sequential information only
Leyi Wei, Pengwei Xing, Jijun Tang, Quan Zou
Many recent efforts have been made for the development of machine learning based methods for fast and accurate phosphorylation site prediction. Currently, a majority of well-performing methods are based on hybrid information to build prediction models, such as evolutionary information,... Read more
Posted on 30 JUL 2017