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Computer-aided diagnosis has become a widely-used auxiliary tool for the diagnosis of Alzheimer's disease (AD). In this study, we developed an extreme learning machine (ELM) model to discriminate between patients with AD and normal controls (NCs) using voxel-based morphometry (VBM) obtained from magnetic resonance imaging. Support vector machine (SVM), Gaussian process regression (GPR), and partial least squares (PLS) regression were compared with the ELM model. The calculated characteristics, i.e., texture features, VBM parameters, and clinical information, were adopted as the classification features. A ten-fold cross validation was used to evaluate the performance of ELM, SVM, GPR, and PLS models. We applied the proposed methods to data from 58 patients with AD and 94 NCs, and achieved a classification accuracy of up to 0.96 with all classification features of the ELM model, while the results of the other three models were 0.82 (PLS), 0.79 (GPR), and 0.75 (SVM). Furthermore, the effect of VBM parameter modeling is better than texture parameter. Thus, our method was optimal in distinguishing patients with AD from NCs, and may therefore be useful for the diagnosis of AD.
This article was published in the following journal.
Alzheimer's disease is a neuropsychiatric, progressive also an ir-reversible disease. There is not an effective cure for the disease. However, early diagnosis has an important role for treatment plann...
With over 35 million cases worldwide, Alzheimer's disease (AD) represents the main cause of dementia. The differentiation of AD from other types of dementia is challenging and its early diagnosis is c...
The article deals with the important issue of diagnosis and treatment of Alzheimer's disease in the elderly and senile age. Despite the fact that this disease is considered, of course, age-associated ...
A probabilistic framework for registering generalised point sets comprising multiple voxel-wise data features such as positions, orientations and scalar-valued quantities, is proposed. It is employed ...
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Aim of the study is to assess the effect of quetiapine treatment in neuroleptic naive, first-episode schizophrenic patients on aspects of functional and structural neuroplasticity assessed...
A multi- and interdisciplinary field concerned with improving health and achieving equity in health for all people. It transcends national boundaries, promotes cooperation and collaboration within and beyond health science fields, and combines population-based disease prevention with individually-based patient care.
An approach of practicing medicine with the goal to improve and evaluate patient care. It requires the judicious integration of best research evidence with the patient's values to make decisions about medical care. This method is to help physicians make proper diagnosis, devise best testing plan, choose best treatment and methods of disease prevention, as well as develop guidelines for large groups of patients with the same disease. (from JAMA 296 (9), 2006)
Prejudice or discrimination based on gender or behavior or attitudes that foster stereotyped social roles based on gender.
Process of formulating a diagnosis based on medical history and physical or mental examinations, and/or choosing an appropriate intervention.
A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations.
Neurology - Central Nervous System (CNS)
Alzheimer's Disease Anesthesia Anxiety Disorders Autism Bipolar Disorders Dementia Epilepsy Multiple Sclerosis (MS) Neurology Pain Parkinson's Disease Sleep Disorders Neurology is the branch of me...