AIMC Topic: Support Vector Machine

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Characterization and classification of asthmatic wheeze sounds according to severity level using spectral integrated features.

Computers in biology and medicine
OBJECTIVE: This study aimed to investigate and classify wheeze sounds of asthmatic patients according to their severity level (mild, moderate and severe) using spectral integrated (SI) features.

A Machine Learning Shock Decision Algorithm for Use During Piston-Driven Chest Compressions.

IEEE transactions on bio-medical engineering
GOAL: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation (CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The best current methods are computationally demanding, and their accuracy ...

Patch-based classification of thyroid nodules in ultrasound images using direction independent features extracted by two-threshold binary decomposition.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Ultrasound imaging of the thyroid gland is considered to be the best diagnostic choice for evaluating thyroid nodules in early stages, since it has been marked as cost-effective, non-invasive and risk-free. Computer aided diagnosis (CAD) systems can ...

Tuning parameter estimation in SCAD-support vector machine using firefly algorithm with application in gene selection and cancer classification.

Computers in biology and medicine
In cancer classification, gene selection is one of the most important bioinformatics related topics. The selection of genes can be considered to be a variable selection problem, which aims to find a small subset of genes that has the most discriminat...

Toward analyzing and synthesizing previous research in early prediction of cardiac arrest using machine learning based on a multi-layered integrative framework.

Journal of biomedical informatics
BACKGROUND: One of the significant problems in the field of healthcare is the low survival rate of people who have experienced sudden cardiac arrest. Early prediction of cardiac arrest can provide the time required for intervening and preventing its ...

A Machine-Learning Approach for Detection and Quantification of QRS Fragmentation.

IEEE journal of biomedical and health informatics
OBJECTIVE: Fragmented QRS (fQRS) is an accessible biomarker and indication of myocardial scarring that can be detected from the electrocardiogram (ECG). Nowadays, fQRS scoring is done on a visual basis, which is time consuming and leads to subjective...

Towards automatic encoding of medical procedures using convolutional neural networks and autoencoders.

Artificial intelligence in medicine
Classification systems such as ICD-10 for diagnoses or the Swiss Operation Classification System (CHOP) for procedure classification in the clinical treatment are essential for clinical management and information exchange. Traditionally, classificati...

Exploiting the heightened phase synchrony in patients with neuromuscular disease for the establishment of efficient motor imagery BCIs.

Journal of neuroengineering and rehabilitation
BACKGROUND: Phase synchrony has extensively been studied for understanding neural coordination in health and disease. There are a few studies concerning the implications in the context of BCIs, but its potential for establishing a communication chann...

A systematic literature review and classification of knowledge discovery in traditional medicine.

Computer methods and programs in biomedicine
INTRODUCTION AND OBJECTIVE: Despite the importance of machine learning methods application in traditional medicine there is a no systematic literature review and a classification for this field. This is the first comprehensive literature review of th...

Boosted feature selectors: a case study on prediction P-gp inhibitors and substrates.

Journal of computer-aided molecular design
Feature selection is commonly used as a preprocessing step to machine learning for improving learning performance, lowering computational complexity and facilitating model interpretation. This paper proposes the application of boosting feature select...