AIMC Topic: Support Vector Machine

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DANN: a deep learning approach for annotating the pathogenicity of genetic variants.

Bioinformatics (Oxford, England)
UNLABELLED: Annotating genetic variants, especially non-coding variants, for the purpose of identifying pathogenic variants remains a challenge. Combined annotation-dependent depletion (CADD) is an algorithm designed to annotate both coding and non-c...

Prediction of β-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine.

Journal of theoretical biology
β-Lactam class of antibiotics is used as major therapeutic agent against a number of pathogenic microbes. The widespread and indiscriminate use of antibiotics to treat bacterial infection has prompted evolution of several evading mechanisms from the ...

Protein submitochondrial localization from integrated sequence representation and SVM-based backward feature extraction.

Molecular bioSystems
Mitochondrion, a tiny energy factory, plays an important role in various biological processes of most eukaryotic cells. Mitochondrial defection is associated with a series of human diseases. Knowledge of the submitochondrial locations of proteins can...

A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Venous thromboembolisms (VTEs), which include deep vein thrombosis (DVT) and pulmonary embolism (PE), are associated with significant mortality, morbidity, and cost in hospitalized patients. To evaluate the success of preventive measures,...

Appraisal of adaptive neuro-fuzzy computing technique for estimating anti-obesity properties of a medicinal plant.

Computer methods and programs in biomedicine
This research examines the precision of an adaptive neuro-fuzzy computing technique in estimating the anti-obesity property of a potent medicinal plant in a clinical dietary intervention. Even though a number of mathematical functions such as SPSS an...

Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.

IEEE journal of biomedical and health informatics
The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, li...

Deep learning of support vector machines with class probability output networks.

Neural networks : the official journal of the International Neural Network Society
Deep learning methods endeavor to learn features automatically at multiple levels and allow systems to learn complex functions mapping from the input space to the output space for the given data. The ability to learn powerful features automatically i...

Predictive Models Based on Support Vector Machines: Whole-Brain versus Regional Analysis of Structural MRI in the Alzheimer's Disease.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
Decision-making systems trained on structural magnetic resonance imaging data of subjects affected by the Alzheimer's disease (AD) and healthy controls (CTRL) are becoming widespread prognostic tools for subjects with mild cognitive impairment (MCI)....

Modeling analgesic drug interactions using support vector regression: a new approach to isobolographic analysis.

Journal of pharmacological and toxicological methods
BACKGROUND: Modeling drug interactions is important for illustrating combined drug actions and for predicting the pharmacological and/or toxicological effects that can be obtained using combined drug therapy.

PseDNA-Pro: DNA-Binding Protein Identification by Combining Chou's PseAAC and Physicochemical Distance Transformation.

Molecular informatics
Identification of DNA-binding proteins is an important problem in biomedical research as DNA-binding proteins are crucial for various cellular processes. Currently, the machine learning methods achieve the-state-of-the-art performance with different ...