IEEE Journal of Translational Engineering in Health and Medicine

Feature Extraction and Identification of Alzheimer’s Disease based on Latent Factor of Multi-Channel EEG
Alzheimer’s disease is a neurodegenerative disease in old age, early diagnosis will help to delay the progression of the disease. Presently, the features of brain functional diseases can be obtained with EEG analysis, but the relationship between characteristics of EEG... Read more
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Topological Network Analysis of Early Alzheimer’s Disease Based on Resting-State EEG
Previous studies made progress in the early diagnosis of Alzheimer’s disease (AD) using electroencephalography (EEG) without considering EEG connectivity. To fill this gap, we explored significant differences between early AD patients and controls based on frequency domain and spatial properties using functional connectivity in mild cognitive impairment (MCI) and mild AD datasets... Read more
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Multi-Source Transfer Learning via Ensemble Approach for Initial Diagnosis of Alzheimer’s Disease
Alzheimer’s disease (AD) is one of the most common progressive neurodegenerative diseases, and the number of AD patients has increased year after year with the global aging trend. The onset of AD has a long preclinical stage. If doctors can... Read more
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In vivo Visualization of Brain Vasculature in Alzheimer’s Disease Model Mice through High-Resolution Ultrasound Blood Flow Mapping
     Objective: Cerebrovascular disorders are associated with Alzheimer’s disease (AD). Preclinical animal study is necessary for understanding AD pathogenesis and determining its optimal diagnosis and treatment strategies. Conventionally, the cerebral vasculature’s structure is analyzed through histological staining. However, functional analysis of... Read more
Articles, Published Articles
Classification of Alzheimer’s Disease, Mild Cognitive Impairment and Normal Control Subjects Using Resting-State fMRI Based Network Connectivity Analysis
     This paper proposes a robust method for the Alzheimer’s disease (AD), mild cognitive impairment (MCI), and normal control subject classification under size limited fMRI data samples by exploiting the brain network connectivity pattern analysis. First, we select the regions of... Read more
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Histogram-Based Features Selection and Volume Of Interest Ranking For Brain PET Image Classification
    Abstract Positron emission tomography (PET) is a molecular medical imaging modality which is commonly used for neurodegenerative diseases diagnosis. Computer-aided diagnosis, based on medical image analysis, could help quantitative evaluation of brain diseases such as Alzheimer’s disease (AD). A novel method... Read more
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Detecting Dementia through Interactive Computer Avatars
       This paper proposes a new approach to automatically detect dementia. Even though some works have detected dementia from speech and language attributes, most have applied detection using picture descriptions, narratives, and cognitive tasks. In this paper, we propose a new... Read more