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    Multi independent latent component extension of naive Bayes classifier

    , Article Knowledge-Based Systems ; Volume 213 , 2021 ; 09507051 (ISSN) Alizadeh, S. H ; Hediehloo, A ; Harzevili, N. S ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Naive Bayes (NB) classifier ease of use along with its remarkable performance has led many researchers to extend the scope of its applications to real-world domains by relaxing the conditional independence assumption of features given the information about the class variable. However, fulfilling this objective, most of the generalizations, cut their own way through compromising the model's simplicity, make more complex classifiers with a substantial deviation from the original one. Multi Independent Latent Component Naive Bayes Classifier (MILC-NB) leverages a set of latent variables to preserve the overall structure of naive Bayes classifier while rectifying its major restriction. Each... 

    Multi independent latent component extension of naive bayes classifier

    , Article Knowledge-Based Systems ; Volume 213 , 2021 ; 09507051 (ISSN) Alizadeh, S. H ; Hediehloo, A ; Shiri Harzevili, N ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Naive Bayes (NB) classifier ease of use along with its remarkable performance has led many researchers to extend the scope of its applications to real-world domains by relaxing the conditional independence assumption of features given the information about the class variable. However, fulfilling this objective, most of the generalizations, cut their own way through compromising the model's simplicity, make more complex classifiers with a substantial deviation from the original one. Multi Independent Latent Component Naive Bayes Classifier (MILC-NB) leverages a set of latent variables to preserve the overall structure of naive Bayes classifier while rectifying its major restriction. Each... 

    Classification of normal and diseased liver shapes based on spherical harmonics coefficients

    , Article Journal of Medical Systems ; Vol. 38, issue. 5 , April , 2014 ; ISSN: 01485598 Mofrad, F. B ; Zoroofi, R. A ; Tehrani-Fard, A. A ; Akhlaghpoor, S ; Sato, Y ; Sharif University of Technology
    Abstract
    Liver-shape analysis and quantification is still an open research subject. Quantitative assessment of the liver is of clinical importance in various procedures such as diagnosis, treatment planning, and monitoring. Liver-shape classification is of clinical importance for corresponding intra-subject and inter-subject studies. In this research, we propose a novel technique for the liver-shape classification based on Spherical Harmonics (SH) coefficients. The proposed liver-shape classification algorithm consists of the following steps: (a) Preprocessing, including mesh generation and simplification, point-set matching, and surface to template alignment; (b) Liver-shape parameterization,... 

    Urine and serum NMR-based metabolomics in pre-procedural prediction of contrast-induced nephropathy

    , Article Internal and Emergency Medicine ; Volume 15, Issue 1 , 2020 , Pages 95-103 Dalili, N ; Chashmniam, S ; Khoormizi, S. M. H ; Salehi, L ; Jamalian, S. A ; Nafar, M ; Kalantari, S ; Sharif University of Technology
    Springer  2020
    Abstract
    Contrast induced nephropathy (CIN) has been reported to be the third foremost cause of acute renal failure. Metabolomics is a robust technique that has been used to identify potential biomarkers for the prediction of renal damage. We aim to analyze the serum and urine metabolites changes, before and after using contrast for coronary angiography, to determine if metabolomics can predict early development of CIN. 66 patients undergoing elective coronary angiography were eligible for enrollment. Urine and serum samples were collected prior to administration of CM and 72 h post procedure and analyzed by nuclear magnetic resonance. The significant differential metabolites between patients who... 

    Chronic subdural hematoma outcome prediction using logistic regression and an artificial neural network

    , Article Neurosurgical Review ; Volume 32, Issue 4 , 2009 , Pages 479-484 ; 03445607 (ISSN) Abouzari, M ; Rashidi, A ; Zandi Toghani, M ; Behzadi, M ; Asadollahi, M ; Sharif University of Technology
    2009
    Abstract
    Artificial neural networks (ANN) have not been used in chronic subdural hematoma (CSDH) outcome prediction following surgery. We used two methods, namely logistic regression and ANN, to predict using eight variables CSDH outcome as assessed by the Glasgow outcome score (GOS) at discharge. We had 300 patients (213 men and 87 women) and potential predictors were age, sex, midline shift, intracranial air, hematoma density, hematoma thickness, brain atrophy, and Glasgow coma score (GCS). The dataset was randomly divided to three subsets: (1) training set (150 cases), (2) validation set (75 cases), and (3) test set (75 cases). The training and validation sets were combined for regression... 

    Expression analysis of protein inhibitor of activated stat in inflammatory demyelinating polyradiculoneuropathy

    , Article Frontiers in Immunology ; Volume 12 , 2021 ; 16643224 (ISSN) Ghafouri Fard, S ; Hussen, B. M ; Nicknafs, F ; Nazer, N ; Sayad, A ; Taheri, M ; Sharif University of Technology
    Frontiers Media S.A  2021
    Abstract
    Protein inhibitors of activated STAT (PIAS) are involved in the regulation of the JAK/STAT signaling pathway and have interactions with NF-κB, p73 and p53. These proteins regulate immune responses; therefore dysregulation in their expression leads to several immune-mediated disorders. In the present study, we examined expression of PIAS1-4 in peripheral blood of patients with acute/chronic inflammatory demyelinating polyradiculoneuropathy (AIDP/CIDP) compared with healthy subjects. We demonstrated down-regulation of all PIAS genes in both AIDP and CIDP cases compared with controls. Similarly, comparisons in gender-based groups revealed down-regulation of these gene0s in patients of each... 

    Opposite trends of GAS6 and GAS6-AS expressions in breast cancer tissues

    , Article Experimental and Molecular Pathology ; Volume 118 , 2021 ; 00144800 (ISSN) Lavasani, A ; Hussen, B. M ; Taheri, F ; Sattari, A ; Yousefi, H ; Omrani, M. D ; Nazer, N ; Ghafouri Fard, S ; Taheri, M ; Sharif University of Technology
    Academic Press Inc  2021
    Abstract
    Growth arrest-specific gene 6 (GAS6) is a growth factor-like cytokine whose function is related with vitamin K. This protein interacts with receptor tyrosine kinase proteins such as Tyro3, Axl, and TAM Receptor family, therefore affecting the tumorigenic processes via different mechanisms. GAS6-antisense 1 (GAS6-AS1) is a long non-coding RNAs (lncRNAs) that is transcribed from a genomic regions nearby GAS6. This lncRNA is also implicated in the pathobiology of cancer. We intended to judge the role of GAS6 and GAS6-AS1 in the pathogenesis of breast cancer through appraisal of their expression levels in breast cancer tissues and their paired neighboring non-cancerous samples. Expression of...