IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 1, 2017
Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the class...
BACKGROUND: The morphometric analysis of myelinated nerve fibers of peripheral nerves in cross-sectional optical microscopic images is valuable. Several automated methods for nerve fiber identification and segmentation have been reported. This paper ...
PURPOSE: The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid ar...
IEEE transactions on visualization and computer graphics
Aug 29, 2017
Recurrent neural networks, and in particular long short-term memory (LSTM) networks, are a remarkably effective tool for sequence modeling that learn a dense black-box hidden representation of their sequential input. Researchers interested in better ...
IEEE transactions on bio-medical engineering
Aug 24, 2017
OBJECTIVE: Gait analysis of animal disease models can provide valuable insights into in vivo compound effects and thus help in preclinical drug development. The purpose of this paper is to establish a computational gait analysis approach for the Nold...
Studies involving multivariate pattern analysis (MVPA) of BOLD fMRI data generally attribute the success of the information-theoretic approach to BOLD signal contrast on the fine spatial scale of millimeters facilitating the classification or decodin...
IEEE transactions on pattern analysis and machine intelligence
Aug 22, 2017
We address the problem of video classification for facial analysis and human action recognition. We propose a novel weakly supervised learning method that models the video as a sequence of automatically mined, discriminative sub-events (e.g., onset a...
BACKGROUND: Patient data, such as electronic health records or adverse event reporting systems, constitute an essential resource for studying Adverse Drug Events (ADEs). We explore an original approach to identify frequently associated ADEs in subgro...
Journal of the American College of Radiology : JACR
Aug 19, 2017
The development and integration of machine learning/artificial intelligence into routine clinical practice will significantly alter the current practice of radiology. Changes in reimbursement and practice patterns will also continue to affect radiolo...
This study provides a brain-based account of how object concepts at an intermediate (basic) level of specificity are represented, offering an enriched view of what it means for a concept to be a basic-level concept, a research topic pioneered by Rosc...