AIMC Topic: Support Vector Machine

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pDHS-SVM: A prediction method for plant DNase I hypersensitive sites based on support vector machine.

Journal of theoretical biology
DNase I hypersensitive sites (DHSs) are accessible chromatin regions hypersensitive to cleavages by DNase I endonucleases. DHSs are indicative of cis-regulatory DNA elements (CREs), all of which play important roles in global gene expression regulati...

Sequence based predictor for discrimination of enhancer and their types by applying general form of Chou's trinucleotide composition.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Enhancers are pivotal DNA elements, which are widely used in eukaryotes for activation of transcription genes. On the basis of enhancer strength, they are further classified into two groups; strong enhancers and weak enhanc...

Continuous detection of human fall using multimodal features from Kinect sensors in scalable environment.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automatic detection of human fall is a key problem in video surveillance and home monitoring. Existing methods using unimodal data (RGB / depth / skeleton) may suffer from the drawbacks of inadequate lighting condition or u...

Subcellular localization prediction of apoptosis proteins based on evolutionary information and support vector machine.

Artificial intelligence in medicine
OBJECTIVES: In this paper, a high-quality sequence encoding scheme is proposed for predicting subcellular location of apoptosis proteins.

Prediction of dissolved oxygen concentration in hypoxic river systems using support vector machine: a case study of Wen-Rui Tang River, China.

Environmental science and pollution research international
Accurate quantification of dissolved oxygen (DO) is critically important for managing water resources and controlling pollution. Artificial intelligence (AI) models have been successfully applied for modeling DO content in aquatic ecosystems with lim...

Quad-phased data mining modeling for dementia diagnosis.

BMC medical informatics and decision making
BACKGROUND: The number of people with dementia is increasing along with people's ageing trend worldwide. Therefore, there are various researches to improve a dementia diagnosis process in the field of computer-aided diagnosis (CAD) technology. The mo...

Robust Grape Detector Based on SVMs and HOG Features.

Computational intelligence and neuroscience
Detection of grapes in real-life images is a serious task solved by researchers dealing with precision viticulture. In the case of white wine varieties, grape detectors based on SVMs classifiers, in combination with a HOG descriptor, have proven to b...

A structured latent model for ovarian carcinoma subtyping from histopathology slides.

Medical image analysis
Accurate subtyping of ovarian carcinomas is an increasingly critical and often challenging diagnostic process. This work focuses on the development of an automatic classification model for ovarian carcinoma subtyping. Specifically, we present a novel...

Comments on prediction of the aqueous solubility using the general solubility equation (GSE) versus a genetic algorithm and a support vector machine model.

Pharmaceutical development and technology
The general solubility equation (GSE) is the state-of-the-art method for estimating the aqueous solubilities of organic compounds. It is an extremely simple equation that expresses aqueous solubility as a function of only two inputs: the octanol-wate...

A Cancer Gene Selection Algorithm Based on the K-S Test and CFS.

BioMed research international
BACKGROUND: To address the challenging problem of selecting distinguished genes from cancer gene expression datasets, this paper presents a gene subset selection algorithm based on the Kolmogorov-Smirnov (K-S) test and correlation-based feature selec...