AIMC Topic: Machine Learning

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Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment.

IEEE transactions on medical imaging
As shown in the literature, methods based on multiple templates usually achieve better performance, compared with those using only a single template for processing medical images. However, most existing multi-template based methods simply average or ...

3D Fast Automatic Segmentation of Kidney Based on Modified AAM and Random Forest.

IEEE transactions on medical imaging
In this paper, a fully automatic method is proposed to segment the kidney into multiple components: renal cortex, renal column, renal medulla and renal pelvis, in clinical 3D CT abdominal images. The proposed fast automatic segmentation method of kid...

Harnessing information from injury narratives in the 'big data' era: understanding and applying machine learning for injury surveillance.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
OBJECTIVE: Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identi...

Two fast and accurate heuristic RBF learning rules for data classification.

Neural networks : the official journal of the International Neural Network Society
This paper presents new Radial Basis Function (RBF) learning methods for classification problems. The proposed methods use some heuristics to determine the spreads, the centers and the number of hidden neurons of network in such a way that the higher...

Probabilistic machine learning for the evaluation of presurgical language dominance.

Journal of neurosurgery
OBJECTIVE Providing a reliable assessment of language lateralization is an important task to be performed prior to neurosurgery in patients with epilepsy. Over the last decade, functional MRI (fMRI) has emerged as a useful noninvasive tool for langua...

Identifying a clinical signature of suicidality among patients with mood disorders: A pilot study using a machine learning approach.

Journal of affective disorders
OBJECTIVE: A growing body of evidence has put forward clinical risk factors associated with patients with mood disorders that attempt suicide. However, what is not known is how to integrate clinical variables into a clinically useful tool in order to...

Predicting Drug-Target Interactions With Multi-Information Fusion.

IEEE journal of biomedical and health informatics
Identifying potential associations between drugs and targets is a critical prerequisite for modern drug discovery and repurposing. However, predicting these associations is difficult because of the limitations of existing computational methods. Most ...

Machine learning based sample extraction for automatic speech recognition using dialectal Assamese speech.

Neural networks : the official journal of the International Neural Network Society
Automatic Speaker Recognition (ASR) and related issues are continuously evolving as inseparable elements of Human Computer Interaction (HCI). With assimilation of emerging concepts like big data and Internet of Things (IoT) as extended elements of HC...

Biosimilarity Assessments of Model IgG1-Fc Glycoforms Using a Machine Learning Approach.

Journal of pharmaceutical sciences
Biosimilarity assessments are performed to decide whether 2 preparations of complex biomolecules can be considered "highly similar." In this work, a machine learning approach is demonstrated as a mathematical tool for such assessments using a variety...

Deep Learning in Drug Discovery.

Molecular informatics
Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical research b...