AIMC Topic: Support Vector Machine

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Training set extension for SVM ensemble in P300-speller with familiar face paradigm.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: P300-spellers are brain-computer interface (BCI)-based character input systems. Support vector machine (SVM) ensembles are trained with large-scale training sets and used as classifiers in these systems. However, the required large-scale ...

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

Cancer genomics & proteomics
Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in h...

[Computer Aided Diagnosis system of breast ultrasound based on support vector machine: a clinical analysis].

Zhonghua yi xue za zhi
To investigate the value of based on support vector machine (SVM) breast ultrasonography technology of Computer-Assisted diagnosis (CAD) for differential diagnosis of benign and malignant breast masses. Total of 143 patients who had 151 breast mass...

[Support vector machine?assisted diagnosis of human malignant gastric tissues based on dielectric properties].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To achieve differential diagnosis of normal and malignant gastric tissues based on discrepancies in their dielectric properties using support vector machine.

SVM-dependent pairwise HMM: an application to protein pairwise alignments.

Bioinformatics (Oxford, England)
MOTIVATION: Methods able to provide reliable protein alignments are crucial for many bioinformatics applications. In the last years many different algorithms have been developed and various kinds of information, from sequence conservation to secondar...

Augmenting intracortical brain-machine interface with neurally driven error detectors.

Journal of neural engineering
OBJECTIVE: Making mistakes is inevitable, but identifying them allows us to correct or adapt our behavior to improve future performance. Current brain-machine interfaces (BMIs) make errors that need to be explicitly corrected by the user, thereby con...

Computer-Aided Diagnosis of Lung Nodules in Computed Tomography by Using Phylogenetic Diversity, Genetic Algorithm, and SVM.

Journal of digital imaging
Lung cancer is pointed as the major cause of death among patients with cancer throughout the world. This work is intended to develop a methodology for diagnosis of lung nodules using images from the Image Database Consortium and Image Database Resour...

CASAnova: a multiclass support vector machine model for the classification of human sperm motility patterns.

Biology of reproduction
The ability to accurately monitor alterations in sperm motility is paramount to understanding multiple genetic and biochemical perturbations impacting normal fertilization. Computer-aided sperm analysis (CASA) of human sperm typically reports motile ...

Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make th...