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    Differentiation of inflammatory papulosquamous skin diseases based on skin biophysical and ultrasonographic properties: A decision tree model

    , Article Indian Journal of Dermatology, Venereology and Leprology ; Volume 86, Issue 6 , 2020 , Pages 752- Yazdanparast, T ; Yazdani, K ; Ahmad Nasrollahi, S ; Nazari, M ; Darooei, R ; Firooz, A ; Sharif University of Technology
    Wolters Kluwer Medknow Publications  2020
    Abstract
    The biophysical and ultrasonographic properties of the skin change in papulosquamous diseases. Aims: To identify biophysical and ultrasonographic properties for the differentiation of five main groups of papulosquamous skin diseases. Methods: Fifteen biophysical and ultrasonographic parameters were measured by multiprobe adapter system and high-frequency ultrasonography in active lesions and normal control skin in patients with chronic eczema, psoriasis, lichen planus, pityriasis rosea and parapsoriasis/mycosis fungoides. Using histological diagnosis as a gold standard, a decision tree analysis was performed based on the mean percentage changes of these parameters [(lesion-control/control)... 

    The Differential Diagnosis of Crohn's Disease and Celiac Disease Using Nuclear Magnetic Resonance Spectroscopy

    , Article Applied Magnetic Resonance ; Volume 45, Issue 5 , May , 2014 , Pages 451-459 Fathi, F ; Kasmaee, L. M ; Sohrabzadeh, K ; Nejad, M. R ; Tafazzoli, M ; Oskouie, A. A ; Sharif University of Technology
    Abstract
    Crohn's disease and celiac disease belong to a group of autoimmune conditions that affect the digestive system, specifically the small intestine. They both attack the digestive tract and share many symptoms. Thus, the discovery of proper methods would be a major step toward differentiating celiac disease from Crohn's disease. The aim of this study was to search for the metabolic biomarkers to differentiate between these two diseases. Proton nuclear magnetic resonance spectroscopy (1H NMR) was employed as the metabolic profiling method to look for serum metabolites that differentiate between celiac disease and Crohn's disease. Classification of celiac disease and Crohn's disease was done... 

    Properties of functional brain networks correlate frequency of psychogenic non-epileptic seizures

    , Article Frontiers in Human Neuroscience ; Issue DEC , 2012 ; 16625161 (ISSN) Barzegaran, E ; Joudaki, A ; Jalili, M ; Rossetti, A. O ; Frackowiak, R. S ; Knyazeva, M. G ; Sharif University of Technology
    Frontiers Media S. A  2012
    Abstract
    Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness metrics, respectively. Yet the number of PNES attacks per month correlated with a... 

    Adaptive neuro-fuzzy inference system for classification of ACL-ruptured knees using arthrometric data

    , Article Annals of Biomedical Engineering ; Volume 36, Issue 9 , 9 July , 2008 , Pages 1449-1457 ; 00906964 (ISSN) Heydari, Z ; Farahmand, F ; Arabalibeik, H ; Parnianpour, M ; Sharif University of Technology
    2008
    Abstract
    A new approach, based on Adaptive-Network-based Fuzzy Inference System (ANFIS), is presented for the classification of arthrometric data of normal/ACL-ruptured knees, considering the insufficiency of existing criteria. An ANFIS classifier was developed and tested on a total of 4800 arthrometric data points collected from 40 normal and 40 injured subjects. The system consisted of 5 layers and 8 rules, based on the results of subtractive data clustering, and trained using the hybrid algorithm method. The performance of the system was evaluated in four runs, in the framework of a 4-fold cross validation algorithm. The results indicated a definite correct diagnosis for typical injured and normal... 

    Interpolation of orientation distribution functions in diffusion weighted imaging using multi-tensor model

    , Article Journal of Neuroscience Methods ; Volume 253 , 2015 , Pages 28-37 ; 01650270 (ISSN) Afzali, M ; Fatemizadeh, E ; Soltanian Zadeh, H ; Sharif University of Technology
    Abstract
    Background: Diffusion weighted imaging (DWI) is a non-invasive method for investigating the brain white matter structure and can be used to evaluate fiber bundles. However, due to practical constraints, DWI data acquired in clinics are low resolution. New method: This paper proposes a method for interpolation of orientation distribution functions (ODFs). To this end, fuzzy clustering is applied to segment ODFs based on the principal diffusion directions (PDDs). Next, a cluster is modeled by a tensor so that an ODF is represented by a mixture of tensors. For interpolation, each tensor is rotated separately. Results: The method is applied on the synthetic and real DWI data of control and...