AIMC Topic: Support Vector Machine

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Prediction error connectivity: A new method for EEG state analysis.

NeuroImage
Several models have been proposed to explain brain regional and interregional communication, the majority of them using methods that tap the frequency domain, like spectral coherence. Considering brain interareal communication as binary interactions,...

Can low-frequency guided waves at the tibia paired with machine learning differentiate between healthy and osteopenic/osteoporotic subjects? A pilot study.

Ultrasonics
PURPOSE: Axial transmission quantitative acoustics (ax-QA) has shown to be a promising tool for assessing bone health and properties in a safe, inexpensive, and portable manner. This study investigated the efficacy of low-frequency ax-QA measured at ...

Advances with support vector machines for novel drug discovery.

Expert opinion on drug discovery
Novel drug discovery remains an enormous challenge, with various computer-aided drug design (CADD) approaches having been widely employed for this purpose. CADD, specifically the commonly used support vector machines (SVMs), can employ machine learni...

MRI Brain Tumour Segmentation Using Hybrid Clustering and Classification by Back Propagation Algorithm.

Asian Pacific journal of cancer prevention : APJCP
Generally the segmentation refers, the partitioning of an image into smaller regions to identify or locate the region of abnormality. Even though image segmentation is the challenging task in medical applications, due to contrary image, local observa...

Discrimination of "hot potato voice" caused by upper airway obstruction utilizing a support vector machine.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: "Hot potato voice" (HPV) is a thick, muffled voice caused by pharyngeal or laryngeal diseases characterized by severe upper airway obstruction, including acute epiglottitis and peritonsillitis. To develop a method for determini...

Toward Automatic Risk Assessment to Support Suicide Prevention.

Crisis
Suicide has been considered an important public health issue for years and is one of the main causes of death worldwide. Despite prevention strategies being applied, the rate of suicide has not changed substantially over the past decades. Suicide ri...

A reliable method for colorectal cancer prediction based on feature selection and support vector machine.

Medical & biological engineering & computing
Colorectal cancer (CRC) is a common cancer responsible for approximately 600,000 deaths per year worldwide. Thus, it is very important to find the related factors and detect the cancer accurately. However, timely and accurate prediction of the diseas...

Efficient sleep classification based on entropy features and a support vector machine classifier.

Physiological measurement
OBJECTIVE: Sleep quality helps to reflect on the physical and mental condition, and efficient sleep stage scoring promises considerable advantages to health care. The aim of this study is to propose a simple and efficient sleep classification method ...

Individual differences in rate of acquiring stable neural representations of tasks in fMRI.

PloS one
Task-related functional magnetic resonance imaging (fMRI) is a widely-used tool for studying the neural processing correlates of human behavior in both healthy and clinical populations. There is growing interest in mapping individual differences in f...

Machine Learning Algorithms Utilizing Functional Respiratory Imaging May Predict COPD Exacerbations.

Academic radiology
RATIONALE AND OBJECTIVES: Acute chronic obstructive pulmonary disease exacerbations (AECOPD) have a significant negative impact on the quality of life and accelerate progression of the disease. Functional respiratory imaging (FRI) has the potential t...