AIMC Topic: Algorithms

Clear Filters Showing 27411 to 27420 of 28713 articles

Adverse drug event and medication extraction in electronic health records via a cascading architecture with different sequence labeling models and word embeddings.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: An adverse drug event (ADE) refers to an injury resulting from medical intervention related to a drug including harm caused by drugs or from the usage of drugs. Extracting ADEs from clinical records can help physicians associate adverse ev...

Ensemble method-based extraction of medication and related information from clinical texts.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Accurate and complete information about medications and related information is crucial for effective clinical decision support and precise health care. Recognition and reduction of adverse drug events is also central to effective patient c...

Protein contact prediction using metagenome sequence data and residual neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Almost all protein residue contact prediction methods rely on the availability of deep multiple sequence alignments (MSAs). However, many proteins from the poorly populated families do not have sufficient number of homologs in the convent...

A study of deep learning approaches for medication and adverse drug event extraction from clinical text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This article presents our approaches to extraction of medications and associated adverse drug events (ADEs) from clinical documents, which is the second track of the 2018 National NLP Clinical Challenges (n2c2) shared task.

Imputation Strategy for Reliable Regional MRI Morphological Measurements.

Neuroinformatics
Regional morphological analysis represents a crucial step in most neuroimaging studies. Results from brain segmentation techniques are intrinsically prone to certain degrees of variability, mainly as results of suboptimal segmentation. To reduce this...

Hierarchical Structured Sparse Learning for Schizophrenia Identification.

Neuroinformatics
Fractional amplitude of low-frequency fluctuation (fALFF) has been widely used for resting-state functional magnetic resonance imaging (rs-fMRI) based schizophrenia (SZ) diagnosis. However, previous studies usually measure the fALFF within low-freque...

Cellular Automata Tractography: Fast Geodesic Diffusion MR Tractography and Connectivity Based Segmentation on the GPU.

Neuroinformatics
Geodesic based tractography on diffusion magnetic resonance data is a method to devise long distance connectivities among the brain regions. In this study, cellular automata technique is applied to the geodesic tractography problem and the algorithm ...

Fusion of ULS Group Constrained High- and Low-Order Sparse Functional Connectivity Networks for MCI Classification.

Neuroinformatics
Functional connectivity networks, derived from resting-state fMRI data, have been found as effective biomarkers for identifying mild cognitive impairment (MCI) from healthy elderly. However, the traditional functional connectivity network is essentia...

LOCALIZATION OF IONIZING RADIATION SOURCES VIA AN AUTONOMOUS ROBOTIC SYSTEM.

Radiation protection dosimetry
The article discusses an autonomous and flexible robotic system for radiation monitoring. The detection part of the system comprises two NaI(Tl) scintillation detectors: one of these is collimated to allow directionally sensitive measurements and the...