Combinatorial chemistry & high throughput screening
Jan 1, 2017
BACKGROUND: One key step in the development of inhibitors for an enzyme is the application of computational methodologies to predict protein-ligand interactions. The abundance of structural and ligand-binding information for HIV-1 protease opens up t...
Radiographics : a review publication of the Radiological Society of North America, Inc
Jan 1, 2017
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapp...
Advances in experimental medicine and biology
Jan 1, 2017
Traditional diagnoses on addiction reply on the patients' self-reports, which are easy to be dampened by false memory or malingering. Machine learning (ML) is a data-driven procedure that learns algorithms from training data and makes predictions. It...
IEEE/ACM transactions on computational biology and bioinformatics
Jan 1, 2017
While the multiple sequence alignment output by an aligner strongly depends on the parameter values used for the alignment scoring function (such as the choice of gap penalties and substitution scores), most users rely on the single default parameter...
IEEE/ACM transactions on computational biology and bioinformatics
Jan 1, 2017
Copy number variants (CNVs), including large deletions and duplications, represent an unbalanced change of DNA segments. Abundant in human genomes, CNVs contribute to a large proportion of human genetic diversity, with impact on many human phenotypes...
Alzheimer disease and associated disorders
Jan 1, 2017
BACKGROUND: Understanding whether the cognitive profile of a patient indicates mild cognitive impairment (MCI) or performance levels within normality is often a clinical challenge. The use of resting-state functional magnetic resonance imaging (RS-fM...
Studies in health technology and informatics
Jan 1, 2017
Fine-meshed perioperative measurements are offering enormous potential for automatically investigating clinical complications during general anesthesia. In this study, we employed multiple machine learning methods to model perioperative hypoxia and c...
Studies in health technology and informatics
Jan 1, 2017
The purpose of this work is to evaluate methods from deep learning for application to Magnetic Resonance Fingerprinting (MRF). MRF is a recently proposed measurement technique for generating quantitative parameter maps. In MRF a non-steady state sign...
Studies in health technology and informatics
Jan 1, 2017
The possibility of auto evaluation of reading and writing difficulties was investigated using non-parametric machine learning (ML) regression technique for URAWSS (Understanding Reading and Writing Skills of Schoolchildren) [1] test data of 168 child...
Studies in health technology and informatics
Jan 1, 2017
This paper describes the initial results of work to create a recommender system to match technology products to people with I/DD by applying machine learning to a large volume of data about: people with I/DD; the technology products they use; and the...
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