AIMC Topic:
Supervised Machine Learning
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Learning and combining image neighborhoods using random forests for neonatal brain disease classification.
Medical image analysis
Aug 9, 2017
It is challenging to characterize and classify normal and abnormal brain development during early childhood. To reduce the complexity of heterogeneous data population, manifold learning techniques are increasingly applied, which find a low-dimensiona...
Matrix and Tensor Completion on a Human Activity Recognition Framework.
IEEE journal of biomedical and health informatics
Aug 7, 2017
Sensor-based activity recognition is encountered in innumerable applications of the arena of pervasive healthcare and plays a crucial role in biomedical research. Nonetheless, the frequent situation of unobserved measurements impairs the ability of m...
Combination of mass spectrometry-based targeted lipidomics and supervised machine learning algorithms in detecting adulterated admixtures of white rice.
Food research international (Ottawa, Ont.)
Aug 4, 2017
The mixing of extraneous ingredients with original products is a common adulteration practice in food and herbal medicines. In particular, authenticity of white rice and its corresponding blended products has become a key issue in food industry. Acco...
TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.
Scientific reports
Jul 31, 2017
Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untapped resource, and thus facilitate the discovery of informative covariates from unstructured clinical n...
Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning.
Environmental science & technology
Jul 25, 2017
Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic activities in marine environments. Traditionally, marine biomonitoring involves the sorting and morphological identification of benthic macro-invertebrates, which ...
Efficient dynamic graph construction for inductive semi-supervised learning.
Neural networks : the official journal of the International Neural Network Society
Jul 24, 2017
Most of graph construction techniques assume a transductive setting in which the whole data collection is available at construction time. Addressing graph construction for inductive setting, in which data are coming sequentially, has received much le...
Protein asparagine deamidation prediction based on structures with machine learning methods.
PloS one
Jul 21, 2017
Chemical stability is a major concern in the development of protein therapeutics due to its impact on both efficacy and safety. Protein "hotspots" are amino acid residues that are subject to various chemical modifications, including deamidation, isom...
Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows.
BMC medical informatics and decision making
Jul 19, 2017
BACKGROUND: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patient...
Multi-modal discriminative dictionary learning for Alzheimer's disease and mild cognitive impairment.
Computer methods and programs in biomedicine
Jul 18, 2017
BACKGROUND AND OBJECTIVE: The differentiation of mild cognitive impairment (MCI), which is the prodromal stage of Alzheimer's disease (AD), from normal control (NC) is important as the recent research emphasis on early pre-clinical stage for possible...
Automated gesture tracking in head-fixed mice.
Journal of neuroscience methods
Jul 17, 2017
BACKGROUND: The preparation consisting of a head-fixed mouse on a spherical or cylindrical treadmill offers unique advantages in a variety of experimental contexts. Head fixation provides the mechanical stability necessary for optical and electrophys...
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