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Accurate classification of brain gliomas by discriminate dictionary learning based on projective dictionary pair learning of proton magnetic resonance spectra.

Magnetic resonance in chemistry : MRC
Proton magnetic resonance spectroscopy is a powerful noninvasive technique that complements the structural images of cMRI, which aids biomedical and clinical researches, by identifying and visualizing the compositions of various metabolites within th...

Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia.

Human brain mapping
Despite decades of research, the anatomical abnormalities associated with developmental dyslexia are still not fully described. Studies have focused on between-group comparisons in which different neuroanatomical measures were generally explored in i...

Prediction of anti-cancer drug response by kernelized multi-task learning.

Artificial intelligence in medicine
MOTIVATION: Chemotherapy or targeted therapy are two of the main treatment options for many types of cancer. Due to the heterogeneous nature of cancer, the success of the therapeutic agents differs among patients. In this sense, determination of chem...

Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is still an area of active research. Several multi-view learning methods have recently been developed to deal with missing data, with each view correspondi...

Using administrative data to identify U.S. Army soldiers at high-risk of perpetrating minor violent crimes.

Journal of psychiatric research
Growing concerns exist about violent crimes perpetrated by U.S. military personnel. Although interventions exist to reduce violent crimes in high-risk populations, optimal implementation requires evidence-based targeting. The goal of the current stud...

Parkinson's disease classification using gait analysis via deterministic learning.

Neuroscience letters
Gait analysis plays an important role in maintaining the well-being of human mobility and health care, and is a valuable tool for obtaining quantitative information on motor deficits in Parkinson's disease (PD). In this paper, we propose a method to ...

A Realistic Seizure Prediction Study Based on Multiclass SVM.

International journal of neural systems
A patient-specific algorithm, for epileptic seizure prediction, based on multiclass support-vector machines (SVM) and using multi-channel high-dimensional feature sets, is presented. The feature sets, combined with multiclass classification and post-...

Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data.

NeuroImage
Machine learning approaches have been widely used for the identification of neuropathology from neuroimaging data. However, these approaches require large samples and suffer from the challenges associated with multi-site, multi-protocol data. We prop...

A knowledge-based expert rule system for predicting mutagenicity (Ames test) of aromatic amines and azo compounds.

Toxicology
Cancer is one of the main causes of death in Western countries, and a major issue for human health. Prolonged exposure to a number of chemicals was observed to be one of the primary causes of cancer in occupationally exposed persons. Thus, the develo...

Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

Annals of the New York Academy of Sciences
Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuo...