AIMC Topic: Support Vector Machine

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Computer-Aided Diagnosis of Micro-Malignant Melanoma Lesions Applying Support Vector Machines.

BioMed research international
Background. One of the fatal disorders causing death is malignant melanoma, the deadliest form of skin cancer. The aim of the modern dermatology is the early detection of skin cancer, which usually results in reducing the mortality rate and less exte...

Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

Waste management (New York, N.Y.)
Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of ...

Topic detection using paragraph vectors to support active learning in systematic reviews.

Journal of biomedical informatics
Systematic reviews require expert reviewers to manually screen thousands of citations in order to identify all relevant articles to the review. Active learning text classification is a supervised machine learning approach that has been shown to signi...

tarSVM: Improving the accuracy of variant calls derived from microfluidic PCR-based targeted next generation sequencing using a support vector machine.

BMC bioinformatics
BACKGROUND: Targeted sequencing of discrete gene sets is a cost effective strategy to screen subjects for monogenic forms of disease. One method to achieve this pairs microfluidic PCR with next generation sequencing. The PCR step of this pipeline cre...

GGIP: Structure and sequence-based GPCR-GPCR interaction pair predictor.

Proteins
G Protein-Coupled Receptors (GPCRs) are important pharmaceutical targets. More than 30% of currently marketed pharmaceutical medicines target GPCRs. Numerous studies have reported that GPCRs function not only as monomers but also as homo- or hetero-d...

Bi-convex Optimization to Learn Classifiers from Multiple Biomedical Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
The problem of constructing classifiers from multiple annotators who provide inconsistent training labels is important and occurs in many application domains. Many existing methods focus on the understanding and learning of the crowd behaviors. Sever...

Sequence Learning with Passive RFID Sensors for Real-Time Bed-Egress Recognition in Older People.

IEEE journal of biomedical and health informatics
Getting out of bed and ambulating without supervision is identified as one of the major causes of patient falls in hospitals and nursing homes. Therefore, increased supervision is proposed as a key strategy toward falls prevention. An emerging genera...

Development of a Support Vector Machine-Based System to Predict Whether a Compound Is a Substrate of a Given Drug Transporter Using Its Chemical Structure.

Journal of pharmaceutical sciences
The aim of this study was to develop an in silico prediction system to assess which of 7 categories of drug transporters (organic anion transporting polypeptide [OATP] 1B1/1B3, multidrug resistance-associated protein [MRP] 2/3/4, organic anion transp...

Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization.

Computational and mathematical methods in medicine
Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this st...