AIMC Topic: Algorithms

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Integrating biological knowledge based on functional annotations for biclustering of gene expression data.

Computer methods and programs in biomedicine
Gene expression data analysis is based on the assumption that co-expressed genes imply co-regulated genes. This assumption is being reformulated because the co-expression of a group of genes may be the result of an independent activation with respect...

Predictive modeling in pediatric traumatic brain injury using machine learning.

BMC medical research methodology
BACKGROUND: Pediatric traumatic brain injury (TBI) constitutes a significant burden and diagnostic challenge in the emergency department (ED). While large North American research networks have derived clinical prediction rules for the head injured ch...

Prediction of cancer proteins by integrating protein interaction, domain frequency, and domain interaction data using machine learning algorithms.

BioMed research international
Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of...

Sentiment analysis using common-sense and context information.

Computational intelligence and neuroscience
Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the r...

Kernel temporal differences for neural decoding.

Computational intelligence and neuroscience
We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. T...

Peaking-Free Output-Feedback Adaptive Neural Control Under a Nonseparation Principle.

IEEE transactions on neural networks and learning systems
High-gain observers have been extensively applied to construct output-feedback adaptive neural control (ANC) for a class of feedback linearizable uncertain nonlinear systems under a nonlinear separation principle. Yet due to static-gain and linear pr...

DEEPEN: A negation detection system for clinical text incorporating dependency relation into NegEx.

Journal of biomedical informatics
In Electronic Health Records (EHRs), much of valuable information regarding patients' conditions is embedded in free text format. Natural language processing (NLP) techniques have been developed to extract clinical information from free text. One cha...

Bridging a translational gap: using machine learning to improve the prediction of PTSD.

BMC psychiatry
BACKGROUND: Predicting Posttraumatic Stress Disorder (PTSD) is a pre-requisite for targeted prevention. Current research has identified group-level risk-indicators, many of which (e.g., head trauma, receiving opiates) concern but a subset of survivor...

Automatic detection of atrial fibrillation using stationary wavelet transform and support vector machine.

Computers in biology and medicine
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Automatic detection of AF could substantially help in early diagnosis, management and co...

USI: a fast and accurate approach for conceptual document annotation.

BMC bioinformatics
BACKGROUND: Semantic approaches such as concept-based information retrieval rely on a corpus in which resources are indexed by concepts belonging to a domain ontology. In order to keep such applications up-to-date, new entities need to be frequently ...