BACKGROUND: Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very la...
A supervised machine learning algorithm, which is qualified for image classification and analyzing similarities, is based on multiple discriminative morphological features that are automatically assembled during the learning processes. The algorithm ...
Computational intelligence and neuroscience
Mar 9, 2016
Although brain-computer interface technology is mainly designed with disabled people in mind, it can also be beneficial to healthy subjects, for example, in gaming or virtual reality systems. In this paper we discuss the typical architecture, paradig...
Robust and fast solutions for anatomical object detection and segmentation support the entire clinical workflow from diagnosis, patient stratification, therapy planning, intervention and follow-up. Current state-of-the-art techniques for parsing volu...
Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper convergence. A promising alternative is to fine-tune a CNN that ha...
Proceedings of the National Academy of Sciences of the United States of America
Mar 7, 2016
Understanding the extremely variable, complex shape and venation characters of angiosperm leaves is one of the most challenging problems in botany. Machine learning offers opportunities to analyze large numbers of specimens, to discover novel leaf fe...
Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these disc...
BACKGROUND: Information about drug-drug interactions (DDIs) is crucial for computational applications such as pharmacovigilance and drug repurposing. However, existing sources of DDIs have the problems of low coverage, low accuracy and low agreement....
An ongoing challenge in the application of gait analysis to clinical settings is the standardized detection of temporal events, with unobtrusive and cost-effective equipment, for a wide range of gait types. The purpose of the current study was to inv...
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