AIMC Topic: Machine Learning

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Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.

Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc Oct 3, 2016
Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. ...
Female Animals Male Lymphoma Machine Learning Algorithms Inflammatory Bowel Diseases Blood Cell Count Cats Cat Diseases Diagnostic Techniques and Procedures Decision Trees Bayes Theorem Blood Chemical Analysis Neural Networks, Computer
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Prediction of anti-cancer drug response by kernelized multi-task learning.

Artificial intelligence in medicine Oct 3, 2016
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...
Forecasting Databases, Factual Computer Simulation Neoplasms Humans Machine Learning Algorithms Antineoplastic Agents Cell Line, Tumor Drug Resistance, Neoplasm
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Outcome Prediction for Patient with High-Grade Gliomas from Brain Functional and Structural Networks.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Oct 2, 2016
High-grade glioma (HGG) is a lethal cancer, which is characterized by very poor prognosis. To help optimize treatment strategy, accurate preoperative prediction of HGG patient's outcome (i.e., survival time) is of great clinical value. However, there...
Diffusion Tensor Imaging Sensitivity and Specificity Brain Neoplasm Grading Brain Neoplasms Glioma Life Expectancy Humans Retrospective Studies Connectome Magnetic Resonance Imaging Treatment Outcome Machine Learning Reproducibility of Results Algorithms
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A Hybrid Multishape Learning Framework for Longitudinal Prediction of Cortical Surfaces and Fiber Tracts Using Neonatal Data.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Oct 2, 2016
Dramatic changes of the human brain during the first year of postnatal development are poorly understood due to their multifold complexity. In this paper, we present the first attempt to jointly predict, using neonatal data, the dynamic growth patter...
Cerebral Cortex Infant Functional Neuroimaging Imaging, Three-Dimensional Infant, Newborn Reproducibility of Results Sensitivity and Specificity Machine Learning Algorithms Humans
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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 Oct 2, 2016
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...
Multimodal Imaging Area Under Curve Alzheimer Disease Positron-Emission Tomography Disease Progression Cognitive Dysfunction Magnetic Resonance Imaging Humans Machine Learning Reproducibility of Results Sensitivity and Specificity Algorithms Databases, Factual
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The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track.

Database : the journal of biological databases and curation Oct 2, 2016
Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the...
Programming Languages Machine Learning Models, Biological Data Mining
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ASAP: a machine learning framework for local protein properties.

Database : the journal of biological databases and curation Oct 2, 2016
Determining residue-level protein properties, such as sites of post-translational modifications (PTMs), is vital to understanding protein function. Experimental methods are costly and time-consuming, while traditional rule-based computational methods...
Internet Molecular Sequence Annotation Sequence Analysis, Protein Machine Learning Peptides
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A machine learning-based framework to identify type 2 diabetes through electronic health records.

International journal of medical informatics Oct 1, 2016
OBJECTIVE: To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects wit...
Humans Pilot Projects Genome-Wide Association Study Bayes Theorem Machine Learning Diabetes Mellitus, Type 2 Logistic Models Algorithms Support Vector Machine Electronic Health Records
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Using administrative data to identify U.S. Army soldiers at high-risk of perpetrating minor violent crimes.

Journal of psychiatric research Sep 30, 2016
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...
Machine Learning Databases, Factual Female Male Adolescent Young Adult Adult Humans Area Under Curve United States Incidence Violence Socioeconomic Factors Military Personnel Models, Theoretical Time Factors Risk Regression Analysis ROC Curve
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Brain-Computer Interface for Control of Wheelchair Using Fuzzy Neural Networks.

BioMed research international Sep 29, 2016
The design of brain-computer interface for the wheelchair for physically disabled people is presented. The design of the proposed system is based on receiving, processing, and classification of the electroencephalographic (EEG) signals and then perfo...
Machine Learning Wheelchairs Brain Mapping Pattern Recognition, Automated Neural Networks, Computer Fuzzy Logic Electroencephalography Brain-Computer Interfaces Man-Machine Systems
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