AIMC Topic: Support Vector Machine

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Action Recognition, Tracking, and Optimization Analysis of Training Process Based on the Support Vector Regression Model.

Journal of healthcare engineering
In order to study the action recognition, tracking, and optimization of the training process based on the support vector regression model, a method of human action recognition based on support vector machine optimization is proposed. This method uses...

Tuberculosis Disease Diagnosis Based on an Optimized Machine Learning Model.

Journal of healthcare engineering
Computer science plays an important role in modern dynamic health systems. Given the collaborative nature of the diagnostic process, computer technology provides important services to healthcare professionals and organizations, as well as to patients...

Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery.

Journal of computer-aided molecular design
The support vector machine (SVM) algorithm is one of the most widely used machine learning (ML) methods for predicting active compounds and molecular properties. In chemoinformatics and drug discovery, SVM has been a state-of-the-art ML approach for ...

Predicting Breast Cancer Based on Optimized Deep Learning Approach.

Computational intelligence and neuroscience
Breast cancer is a dangerous disease with a high morbidity and mortality rate. One of the most important aspects in breast cancer treatment is getting an accurate diagnosis. Machine-learning (ML) and deep learning techniques can help doctors in makin...

Automatic detection of arrhythmias from an ECG signal using an auto-encoder and SVM classifier.

Physical and engineering sciences in medicine
Millions of people around the world are affected by arrhythmias, which are abnormal activities of the functioning of the heart. Most arrhythmias are harmful to the heart and can suddenly become life-threatening. The electrocardiogram (ECG) is an impo...

Verhulst map measures: new biomarkers for heart rate classification.

Physical and engineering sciences in medicine
Recording, monitoring, and analyzing biological signals has received significant attention in medicine. A fundamental phase for understanding a bio-system under various conditions is to process the corresponding bio-signal appropriately. To this effe...

Improving multiple model ensemble predictions of daily precipitation and temperature through machine learning techniques.

Scientific reports
Multi-Model Ensembles (MMEs) are used for improving the performance of GCM simulations. This study evaluates the performance of MMEs of precipitation, maximum temperature and minimum temperature over a tropical river basin in India developed by vario...

Research on exercise fatigue estimation method of Pilates rehabilitation based on ECG and sEMG feature fusion.

BMC medical informatics and decision making
PURPOSE: Surface electromyography (sEMG) is vulnerable to environmental interference, low recognition rate and poor stability. Electrocardiogram (ECG) signals with rich information were introduced into sEMG to improve the recognition rate of fatigue ...

A Machine-Learning-Based Medical Imaging Fast Recognition of Injury Mechanism for Athletes of Winter Sports.

Frontiers in public health
The Beijing 2022 Winter Olympics will begin soon, which is mainly focused on winter sports. Athletes from different countries will arrive in Beijing one after another for training and competition. The health protection of athletes of winter sports is...

PlatypOUs-A Mobile Robot Platform and Demonstration Tool Supporting STEM Education.

Sensors (Basel, Switzerland)
Given the rising popularity of robotics, student-driven robot development projects are playing a key role in attracting more people towards engineering and science studies. This article presents the early development process of an open-source mobile ...