support vector machine

Classifying multi-level stress responses from brain cortical EEG in Nurses and Non-health professionals using Machine Learning Auto Encoder
Author(s)3: Ashlesha Akella, Avinash Kumar Singh, Daniel Leong, Sara Lal, Phillip Newton, Roderick Clifton-Bligh, Craig Steven McLachlan, Sylvia Maria Gustin, Shamona Maharaj, Ty Lees, Zehong Cao, Chin-Teng Lin
Classifying multi-level stress responses from brain cortical EEG in Nurses and Non-health professionals using Machine Learning Auto Encoder 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Objective: Mental stress is a major problem in our society and has become an area of interest for many psychiatric researchers. One primary research focus area is the identification of…

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A 12-Lead ECG-Based System With Physiological Parameters and Machine Learning to Identify Right Ventricular Hypertrophy in Young Adults
Author(s)3: Gen-Min Lin, Henry Horng-Shing Lu
A 12-Lead ECG-Based System With Physiological Parameters and Machine Learning to Identify Right Ventricular Hypertrophy in Young Adults 675 601 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

The presence of right ventricular hypertrophy (RVH) accounts for approximately 5-10% in young adults. The sensitivity estimated by commonly used 12-lead electrocardiographic (ECG) criteria for identifying the presence of RVH…

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The identification of Alzheimer’s disease using functional connectivity between activity voxels in resting-state fMRI data
Author(s)3: Yuhu Shi, Weiming Zeng, Jin Deng, Weifang Nie, Yifei Zhang
The identification of Alzheimer’s disease using functional connectivity between activity voxels in resting-state fMRI data 872 397 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Alzheimer’s disease (AD) is a common neurodegenerative disease occurring in the elderly population. The effective and accurate classification of AD symptoms by using functional magnetic resonance imaging (fMRI) has a…

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Multiple Linear Discriminant Models for Extracting Salient Characteristic Patterns in Capsule Endoscopy Images for Multi-Disease Detection
Author(s)3: Amit Kumar Kundu, Khanh A. Wahid, Shaikh Anowarul Fattah
Multiple Linear Discriminant Models for Extracting Salient Characteristic Patterns in Capsule Endoscopy Images for Multi-Disease Detection 698 659 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Background: Computer-aided disease detection schemes from wireless capsule endoscopy (WCE) videos have received great attention by the researchers for reducing physicians’ burden due to the time-consuming and risky manual review…

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A Multi-Classifier System for Automatic Mitosis Detection in Breast Histopathology Images using Deep Belief Networks

A Multi-Classifier System for Automatic Mitosis Detection in Breast Histopathology Images using Deep Belief Networks
Author(s)3: Sabeena Beevi K, Madhu S. Nair, Bindu G. R.
A Multi-Classifier System for Automatic Mitosis Detection in Breast Histopathology Images using Deep Belief Networks 780 331 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Mitotic count is an important diagnostic factor in breast cancer grading and prognosis. Detection of mitosis in breast histopathology images is very challenging mainly due to diffused intensities along object…

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