A Tensor-Based Framework for rs-fMRI Classification and Functional Connectivity Construction

construction and validation of a computerized adaptive translation test (a receptive based study)

آزمون انطباقی رایانه ای (cat) روشی نوین برای سنجش سطح علمی دانش آموزان می باشد. در حقیقت آزمون های رایانه ای با سرعت بالایی به سمت و سوی جایگزین عملی برای آزمون های کاغذی می روند (کینگزبری، هاوسر، 1993). مقاله حاضر به دنبال آزمون انطباقی رایانه ای برای ترجمه می باشد. بدین منظور دو پرسشنامه مشتمل بر 55 تست ترجمه میان 102 آزمودنی و 10 مدرس زبان انگلیسی پخش گردید. پرسشنامه اول میان 102 دانشجوی س...

Learning Tensor-Based Features for Whole-Brain fMRI Classification

This paper presents a novel tensor-based feature learning approach for whole-brain fMRI classification. Whole-brain fMRI data have high exploratory power, but they are challenging to deal with due to large numbers of voxels. A critical step for fMRI classification is dimensionality reduction, via feature selection or feature extraction. Most current approaches perform voxel selection based on f...

Identification of mild cognitive impairment disease using brain functional connectivity and graph analysis in fMRI data

Background: Early diagnosis of patients in the early stages of Alzheimer's, known as mild cognitive impairment, is of great importance in the treatment of this disease. If a patient can be diagnosed at this stage, it is possible to treat or delay Alzheimer's disease. Resting-state functional magnetic resonance imaging (fMRI) is very common in the process of diagnosing Alzheimer's disease. In th...

Support vector classification analysis of resting state functional connectivity fMRI

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classifica...