AIMC Topic: Algorithms

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Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses.

BMC genomics
BACKGROUND: Pathway analysis has been widely used to gain insight into essential mechanisms of the response to myocardial infarction (MI). Currently, there exist multiple pathway databases that organize molecular datasets and manually curate pathway ...

Early identification of posttraumatic stress following military deployment: Application of machine learning methods to a prospective study of Danish soldiers.

Journal of affective disorders
BACKGROUND: Pre-deployment identification of soldiers at risk for long-term posttraumatic stress psychopathology after home coming is important to guide decisions about deployment. Early post-deployment identification can direct early interventions t...

Domain adaptation for semantic role labeling of clinical text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Semantic role labeling (SRL), which extracts a shallow semantic relation representation from different surface textual forms of free text sentences, is important for understanding natural language. Few studies in SRL have been conducted in...

A Further Study on Mining DNA Motifs Using Fuzzy Self-Organizing Maps.

IEEE transactions on neural networks and learning systems
Self-organizing map (SOM)-based motif mining, despite being a promising approach for problem solving, mostly fails to offer a consistent interpretation of clusters with respect to the mixed composition of signal and noise in the nodes. The main reaso...

Machine learning classification of OARSI-scored human articular cartilage using magnetic resonance imaging.

Osteoarthritis and cartilage
OBJECTIVE: The purpose of this study is to evaluate the ability of machine learning to discriminate between magnetic resonance images (MRI) of normal and pathological human articular cartilage obtained under standard clinical conditions.

A new robust model of one-class classification by interval-valued training data using the triangular kernel.

Neural networks : the official journal of the International Neural Network Society
A robust one-class classification model as an extension of Campbell and Bennett's (C-B) novelty detection model on the case of interval-valued training data is proposed in the paper. It is shown that the dual optimization problem to a linear program ...

EMD-Based Temporal and Spectral Features for the Classification of EEG Signals Using Supervised Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper presents a novel method for feature extraction from electroencephalogram (EEG) signals using empirical mode decomposition (EMD). Its use is motivated by the fact that the EMD gives an effective time-frequency analysis of nonstationary sign...

Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury.

Health economics
For a continuous treatment, the generalised propensity score (GPS) is defined as the conditional density of the treatment, given covariates. GPS adjustment may be implemented by including it as a covariate in an outcome regression. Here, the unbiased...