AIMC Topic: Support Vector Machine

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Early-Stage Gas Identification Using Convolutional Long Short-Term Neural Network with Sensor Array Time Series Data.

Sensors (Basel, Switzerland)
Gas identification/classification through pattern recognition techniques based on gas sensor arrays often requires the equilibrium responses or the full traces of time-series data of the sensor array. Leveraging upon the diverse gas sensing kinetics ...

Development of MRI-Based Radiomics Model to Predict the Risk of Recurrence in Patients With Advanced High-Grade Serous Ovarian Carcinoma.

AJR. American journal of roentgenology
The purpose of our study was to develop a radiomics model based on preoperative MRI and clinical information for predicting recurrence-free survival (RFS) in patients with advanced high-grade serous ovarian carcinoma (HGSOC). This retrospective stu...

Combining Genetic Algorithms and SVM for Breast Cancer Diagnosis Using Infrared Thermography.

Sensors (Basel, Switzerland)
Breast cancer is one of the leading causes of mortality globally, but early diagnosis and treatment can increase the cancer survival rate. In this context, thermography is a suitable approach to help early diagnosis due to the temperature difference ...

Instance elimination strategy for non-convex multiple-instance learning using sparse positive bags.

Neural networks : the official journal of the International Neural Network Society
In some multiple instance learning (MIL) applications, positive bags are sparse (i.e. containing only a small fraction of positive instances). To deal with the imbalanced data caused by these situations, we present a novel MIL method based on a small...

The application of feature engineering in establishing a rapid and robust model for identifying patients with glioma.

Lasers in medical science
The aim of the study is to evaluate the efficacy of the combination of Raman spectroscopy with feature engineering and machine learning algorithms for detecting glioma patients. In this study, we used Raman spectroscopy technology to collect serum sp...

CRP (C-Reactive Protein) in Outcome Prediction After Subarachnoid Hemorrhage and the Role of Machine Learning.

Stroke
BACKGROUND AND PURPOSE: Outcome prediction after aneurysmal subarachnoid hemorrhage (aSAH) is challenging. CRP (C-reactive protein) has been reported to be associated with outcome, but it is unclear if this is independent of other predictors and appl...

Predicting HIV drug resistance using weighted machine learning method at target protein sequence-level.

Molecular diversity
Acquired immune deficiency syndrome (AIDS) is a fatal disease caused by human immunodeficiency virus (HIV). Although 23 different drugs have been available, the treatment of AIDS remains challenging because the virus mutates very quickly which can le...

Building a Cardiovascular Disease Prediction Model for Smartwatch Users Using Machine Learning: Based on the Korea National Health and Nutrition Examination Survey.

Biosensors
Smartwatches have the potential to support health care in everyday life by supporting self-monitoring of health conditions and personal activities. This paper aims to develop a model that predicts the prevalence of cardiovascular disease using health...

A Comparative Study of Traffic Classification Techniques for Smart City Networks.

Sensors (Basel, Switzerland)
Smart city networks involve many applications that impose specific Quality of Service (QoS) requirements, thus representing a challenging scenario for network management. Solutions aiming to guarantee QoS support have not been deployed in large-scale...

Machine Learning for Sensorless Temperature Estimation of a BLDC Motor.

Sensors (Basel, Switzerland)
In this article, the authors propose two models for BLDC motor winding temperature estimation using machine learning methods. For the purposes of the research, measurements were made for over 160 h of motor operation, and then, they were preprocessed...