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Support Vector Machine

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Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods.

Scientific reports
Noise-induced hearing loss (NIHL) is a common occupational condition. The aim of this study was to develop a classification model for NIHL on the basis of both functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sM...

Sexual dimorphism of the humerus bones in a French sample: comparison of several statistical models including machine learning models.

International journal of legal medicine
Sex estimation is an important part of skeletal analysis and forensic identification. Traditionally pelvic traits are utilized for accurate sex estimation. However, the long bones, especially humerus, have been proved to be as effective for determine...

Optimized Adaboost Support Vector Machine-Based Encryption for Securing IoT-Cloud Healthcare Data.

Sensors (Basel, Switzerland)
The Internet of Things (IoT) connects various medical devices that enable remote monitoring, which can improve patient outcomes and help healthcare providers deliver precise diagnoses and better service to patients. However, IoT-based healthcare mana...

Age group classification based on optical measurement of brain pulsation using machine learning.

Scientific reports
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monito...

A quantum-optimized approach for breast cancer detection using SqueezeNet-SVM.

Scientific reports
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretatio...

Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.

Scientific reports
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and a...

A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution.

PloS one
Petroleum hydrocarbon pollution causes significant damage to soil, so accurate prediction and early intervention are crucial for sustainable soil management. However, traditional soil analysis methods often rely on statistical methods, which means th...

Integrating Retinal Segmentation Metrics with Machine Learning for Predictions from Mouse SD-OCT Scans.

Current eye research
PURPOSE: This study aimed to initially test whether machine learning approaches could categorically predict two simple biological features, mouse age and mouse species, using the retinal segmentation metrics.

Advancing DNA Structural Analysis: A SERS Approach Free from Citrate Interference Combined with Machine Learning.

The journal of physical chemistry letters
Surface-enhanced Raman spectroscopy (SERS) has become an indispensable tool for biomolecular analysis, yet the detection of DNA signals remains hindered by spectral interference from citrate ions, which overlap with key DNA features. This study intro...

Discrimination of unsound soybeans using hyperspectral imaging: A deep learning method based on dual-channel feature fusion strategy and attention mechanism.

Food research international (Ottawa, Ont.)
The application of high-level data fusion in the detection of agricultural products still presents a significant challenge. In this study, dual-channel feature fusion model (DCFFM) with attention mechanism was proposed to optimize the utilization of ...