AIMC Topic: Support Vector Machine

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Support Vector Machine-based Spontaneous Intracranial Hypotension Detection on Brain MRI.

Clinical neuroradiology
BACKGROUND AND PURPOSE: To develop a fully automatic algorithm for the magnetic resonance imaging (MRI) identification of patients with spontaneous intracranial hypotension (SIH).

Evaluating Performance of EEG Data-Driven Machine Learning for Traumatic Brain Injury Classification.

IEEE transactions on bio-medical engineering
OBJECTIVES: Big data analytics can potentially benefit the assessment and management of complex neurological conditions by extracting information that is difficult to identify manually. In this study, we evaluated the performance of commonly used sup...

Impacts of multicollinearity on CAPT modalities: An heterogeneous machine learning framework for computer-assisted French phoneme pronunciation training.

PloS one
Phoneme pronunciations are usually considered as basic skills for learning a foreign language. Practicing the pronunciations in a computer-assisted way is helpful in a self-directed or long-distance learning environment. Recent researches indicate th...

Natural language processing for cognitive therapy: Extracting schemas from thought records.

PloS one
The cognitive approach to psychotherapy aims to change patients' maladaptive schemas, that is, overly negative views on themselves, the world, or the future. To obtain awareness of these views, they record their thought processes in situations that c...

Prediction of all-cause mortality in coronary artery disease patients with atrial fibrillation based on machine learning models.

BMC cardiovascular disorders
BACKGROUND: Machine learning (ML) can include more diverse and more complex variables to construct models. This study aimed to develop models based on ML methods to predict the all-cause mortality in coronary artery disease (CAD) patients with atrial...

A weighted twin support vector machine as a potential discriminant analysis tool and evaluation of its performance for near-infrared spectroscopic discrimination of the geographical origins of diverse agricultural products.

Talanta
A weighted twin support vector machine (wTWSVM) was proposed as a potential discriminant analysis tool and its utility was evaluated for near-infrared (NIR) spectroscopic identification of the geographical origins of 12 different agricultural product...

Identification of efflux proteins based on contextual representations with deep bidirectional transformer encoders.

Analytical biochemistry
Efflux proteins are the transport proteins expressed in the plasma membrane, which are involved in the movement of unwanted toxic substances through specific efflux pumps. Several studies based on computational approaches have been proposed to predic...

Machine learning-enabled predictive modeling to precisely identify the antimicrobial peptides.

Medical & biological engineering & computing
The ubiquitous antimicrobial peptides (AMPs), with a broad range of antimicrobial activities, represent a great promise for combating the multi-drug resistant infections. In this study, using a large and diverse set of AMPs (2638) and non-AMPs (3700)...

iMPT-FDNPL: Identification of Membrane Protein Types with Functional Domains and a Natural Language Processing Approach.

Computational and mathematical methods in medicine
Membrane protein is an important kind of proteins. It plays essential roles in several cellular processes. Based on the intramolecular arrangements and positions in a cell, membrane proteins can be divided into several types. It is reported that the ...

Development of a proteochemometric-based support vector machine model for predicting bioactive molecules of tubulin receptors.

Molecular diversity
Microtubules are receiving enormous interest in drug discovery due to the important roles they play in cellular functions. Targeting tubulin polymerization presents an excellent opportunity for the development of anti-tubulin drugs. Drug resistance a...