IEEE transactions on pattern analysis and machine intelligence
Nov 22, 2017
Riemannian manifolds have been widely employed for video representations in visual classification tasks including video-based face recognition. The success mainly derives from learning a discriminant Riemannian metric which encodes the non-linear geo...
IEEE transactions on neural networks and learning systems
Nov 22, 2017
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerging as a l...
Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns ...
COPD patients are burdened with a daily risk of acute exacerbation and loss of control, which could be mitigated by effective, on-demand decision support tools. In this study, we present a machine learning-based strategy for early detection of exacer...
IEEE journal of biomedical and health informatics
Nov 20, 2017
The classification of medical images and illustrations from the biomedical literature is important for automated literature review, retrieval, and mining. Although deep learning is effective for large-scale image classification, it may not be the opt...
Pain practice : the official journal of World Institute of Pain
Nov 20, 2017
BACKGROUND: Arthritis is the leading cause of work disability and contributes to lost productivity. Previous studies showed that various factors predict pain, but they were limited in sample size and scope from a data analytics perspective.
Medical & biological engineering & computing
Nov 18, 2017
Impedance cardiography is a low-cost noninvasive technique, based on monitoring of the thoracic impedance, for estimation of stroke volume (SV). Impedance cardiogram (ICG) is the negative of the first derivative of the impedance signal. A technique f...
Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithm...
Journal of the American College of Radiology : JACR
Nov 17, 2017
Much attention has been given to machine learning and its perceived impact in radiology, particularly in light of recent success with image classification in international competitions. However, machine learning is likely to impact radiology outside ...
Modern time series gene expression and other omics data sets have enabled unprecedented resolution of the dynamics of cellular processes such as cell cycle and response to pharmaceutical compounds. In anticipation of the proliferation of time series ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.