AIMC Topic: Databases, Factual

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Permutation entropy analysis of vital signs data for outcome prediction of patients with severe traumatic brain injury.

Computers in biology and medicine
Permutation entropy is computationally efficient, robust to outliers, and effective to measure complexity of time series. We used this technique to quantify the complexity of continuous vital signs recorded from patients with traumatic brain injury (...

ADReCS: an ontology database for aiding standardization and hierarchical classification of adverse drug reaction terms.

Nucleic acids research
Adverse drug reactions (ADRs) are noxious and unexpected effects during normal drug therapy. They have caused significant clinical burden and been responsible for a large portion of new drug development failure. Molecular understanding and in silico ...

Automated structural classification of lipids by machine learning.

Bioinformatics (Oxford, England)
MOTIVATION: Modern lipidomics is largely dependent upon structural ontologies because of the great diversity exhibited in the lipidome, but no automated lipid classification exists to facilitate this partitioning. The size of the putative lipidome fa...

Question answering for biology.

Methods (San Diego, Calif.)
Biologists often pose queries to search engines and biological databases to obtain answers related to ongoing experiments. This is known to be a time consuming, and sometimes frustrating, task in which more than one query is posed and many databases ...

Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data.

Nucleic acids research
The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens ...

Learning curves for robot-assisted and laparoscopic partial nephrectomy.

Journal of endourology
OBJECTIVES: To evaluate the learning curve of robot-assisted partial nephrectomy (RAPN) and laparoscopic partial nephrectomy (LPN) between two surgeons at a single institution.

Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.

NeuroImage
Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be important to identify MCI patients at high risk for conversion to AD. In this s...

Manifold regularized multitask feature learning for multimodality disease classification.

Human brain mapping
Multimodality based methods have shown great advantages in classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint select...

Manifold Adaptive Label Propagation for Face Clustering.

IEEE transactions on cybernetics
In this paper, a novel label propagation (LP) method is presented, called the manifold adaptive label propagation (MALP) method, which is to extend original LP by integrating sparse representation constraint into regularization framework of LP method...

Region based stellate features combined with variable selection using AdaBoost learning in mammographic computer-aided detection.

Computers in biology and medicine
In this paper, a new method is developed for extracting so-called region-based stellate features to correctly differentiate spiculated malignant masses from normal tissues on mammograms. In the proposed method, a given region of interest (ROI) for fe...