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    Findings of DTI-p maps in comparison with T 2 /T 2 -FLAIR to assess postoperative hyper-signal abnormal regions in patients with glioblastoma 08 Information and Computing Sciences 0801 Artificial Intelligence and Image Processing

    , Article Cancer Imaging ; Volume 18, Issue 1 , 2018 ; 14707330 (ISSN) Beigi, M ; Safari, M ; Ameri, A ; Shojaee Moghadam, M ; Arbabi, A ; Tabatabaeefar, M ; Salighehrad, H ; Sharif University of Technology
    BioMed Central Ltd  2018
    Purpose: The aim of this study was to compare diffusion tensor imaging (DTI) isotropic map (p-map) with current radiographically (T 2/T 2 -FLAIR) methods based on abnormal hyper-signal size and location of glioblastoma tumor using a semi-automatic approach. Materials and methods: Twenty-five patients with biopsy-proved diagnosis of glioblastoma participated in this study. T 2, T 2 -FLAIR images and diffusion tensor imaging (DTI) were acquired 1 week before radiotherapy. Hyper-signal regions on T 2, T 2 -FLAIR and DTI p-map were segmented by means of semi-automated segmentation. Manual segmentation was used as ground truth. Dice Scores (DS) were calculated for validation of semiautomatic... 

    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
    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... 

    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
    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... 

    Quantitative in vivo microsampling for pharmacokinetic studies based on an integrated solid-phase microextraction system

    , Article Analytical Chemistry ; Volume 79, Issue 12 , 2007 , Pages 4507-4513 ; 00032700 (ISSN) Zhang, X ; Eshaghi, A ; Musteata, F. M ; Ouyang, G ; Pawliszyn, J ; Sharif University of Technology
    An integrated microsampling approach based on solid-phase microextraction (SPME) was developed to provide a complete solution to highly efficient and accurate pharmacokinetic studies. The microsampling system included SPME probes that are made of poly(ethylene glycol) (PEG) and C18-bonded silica, a fast and efficient sampling strategy with accurate kinetic calibration, and a high-throughput desorption device based on a modified 96-well plate. The sampling system greatly improved the quantitative capability of SPME in two ways. First, the use of the C18-bonded silica/PEG fibers minimized the competition effect from analogues of the target analytes in a complicated sample matrix such as blood... 

    Automated trace determination of earthy-musty odorous compounds in water samples by on-line purge-and-trap-gas chromatography-mass spectrometry

    , Article Journal of Chromatography A ; Volume 1136, Issue 2 , 2006 , Pages 170-175 ; 00219673 (ISSN) Salemi, A ; Lacorte, S ; Bagheri, H ; Barceló, D ; Sharif University of Technology
    An automated technique based on purge-and-trap coupled to gas chromatography with mass spectrometric detection has been developed and optimized for the trace determination of five of the most important water odorants; 2-isopropyl-3-methoxypyrazine, 2-isobutyl-3-methoxypyrazine, 2-methylisoborneol, 2,4,6-trichloroanisole and geosmin. The extraction method was absolutely solvent-free. Analytes were purged from 20 ml of water sample containing sodium chloride at room temperature by a flow of He and trapped on a Tenax sorbent. The desorption step was performed with helium and temperature programming and desorbed analytes were directly transferred to a gas chromatograph coupled to a mass... 

    Assessment of preprocessing on classifiers used in the P300 speller paradigm

    , Article 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, New York, NY, 30 August 2006 through 3 September 2006 ; 2006 , Pages 1319-1322 ; 05891019 (ISSN); 1424400325 (ISBN); 9781424400324 (ISBN) Mirghasemi, H ; Shamsollahi, M. B ; Fazel Rezai, R ; Sharif University of Technology
    Artifact removal is an essential part in electroencephalogram (EEG) recording and the raw EEG signals require preprocessing before feature extraction. In this work, we implemented three filtering methods and demonstrated their effects on the performance of different classifiers. Bandpass digital filtering, median filtering and facet method are three preprocessing approaches investigated in this paper. We used data set lib from the BCI competition 2003 for training and testing phase. Our accuracy varied between 80% and 96%. In our work, we demonstrated that the problems of choosing the classifier and preprocessing methods are not independent of each other. Two of our approaches could achieve... 

    Electrochemical prostate-specific antigen biosensors based on electroconductive nanomaterials and polymers

    , Article Clinica Chimica Acta ; Volume 516 , 2021 , Pages 111-135 ; 00098981 (ISSN) Dowlatshahi, S ; Abdekhodaie, M. J ; Sharif University of Technology
    Elsevier B.V  2021
    Prostate cancer (PCa), the second most malignant neoplasm in men, is also the fifth leading cause of cancer-related deaths in men globally. Unfortunately, this malignancy remains largely asymptomatic until late-stage emergence when treatment is limited due to the lack of effective metastatic PCa therapeutics. Due to these limitations, early PCa detection through prostate-specific antigen (PSA) screening has become increasingly important, resulting in a more than 50% decrease in mortality. Conventional assays for PSA detection, such as enzyme-linked immunosorbent assay (ELISA), are labor intensive, relatively expensive, operator-dependent and do not provide adequate sensitivity.... 

    Comparison of near-infrared (NIR) and mid-infrared (MIR) spectroscopy based on chemometrics for saffron authentication and adulteration detection

    , Article Food Chemistry ; Volume 344 , 2021 ; 03088146 (ISSN) Amirvaresi, A ; Nikounezhad, N ; Amirahmadi, M ; Daraei, B ; Parastar, H ; Sharif University of Technology
    Elsevier Ltd  2021
    In this work, the potential of near-infrared (NIR) and mid-infrared (MIR) spectroscopy along with chemometrics was investigated for authentication and adulteration detection of Iranian saffron samples. First, authentication of one-hundred saffron samples was examined by principal component analysis (PCA). The results showed the NIR spectroscopy can better predict the origin of samples than the MIR. Next, partial least squares-discriminant analysis (PLS-DA) was developed to detect four common plant-derived adulterants (i.e., saffron style, calendula, safflower, and rubia). In all cases, PLS-DA classification figures of merit in terms of sensitivity, specificity, error rate and accuracy were... 

    Abnormal expression of NF-κB-related transcripts in blood of patients with inflammatory peripheral nerve disorders

    , Article Metabolic Brain Disease ; Volume 36, Issue 8 , 2021 , Pages 2369-2376 ; 08857490 (ISSN) Azimi, T ; Ghafouri Fard, S ; Badrlou, E ; Omrani, D ; Nazer, N ; Sayad, A ; Taheri, M ; Sharif University of Technology
    Springer  2021
    The NF-κB family includes some transcription factors which have important functions in the regulation of immune responses, therefore participating in the pathophysiology of inflammatory conditions such as peripheral neuropathies. We have quantified expression of a number of NF-κB-related transcripts in patients with Guillain-Barré syndrome (GBS) or chronic inflammatory demyelinating polyneuropathy (CIDP) versus healthy subjects. These transcripts have been previously shown to be functionally related with this family of transcription factors. Expressions of ATG5, DICER-AS1, PACER, DILC, NKILA and ADINR have been increased in both CIDP and GBS patients compared with controls. However,... 

    Sol-gel-based solid-phase microextraction and gas chromatography-mass spectrometry determination of dextromethorphan and dextrorphan in human plasma

    , Article Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences ; Volume 818, Issue 2 , 2005 , Pages 147-157 ; 15700232 (ISSN) Bagheri, H ; Eshaghi, A ; Rouini, M. R ; Sharif University of Technology
    A novel solid-phase microextraction (SPME) method was developed for isolation of dextromethorphan (DM) and its main metabolite dextrorphan (DP) from human plasma followed by GC-MS determination. Three different polymers, poly(dimethylsiloxane) (PDMS), poly(ethylenepropyleneglycol) monobutyl ether (Ucon) and polyethylene glycol (PEG) were synthesized as coated fibers using sol-gel methodologies. DP was converted to its acetyl-derivative prior to extraction and subsequent determination. The porosity of coated fibers was examined by SEM technique. Effects of different parameters such as fiber coating type, extraction mode, agitation method, sample volume, extraction time, and desorption... 

    Noninvasive detection of coronary artery disease by arterio-oscillo-graphy

    , Article IEEE Transactions on Biomedical Engineering ; Volume 52, Issue 4 , 2005 , Pages 743-747 ; 00189294 (ISSN) Pouladian, M ; Hashemi Golpayegani, M. R ; Abbaspour Tehrani Fard, A ; Bubvay Nejad, M ; Sharif University of Technology
    Coronary artery disease (CAD) causes oscillations in peripheral arteries. Oscillations of the walls of the brachial arteries of 51 patients were recorded [together with the electrocardiogram (ECG)] by an accelerometer at different cuff pressures. By analyzing the energy of the oscillations in the 30-250 Hz band, 16 of 22 patients with CAD and 26 of 29 non-CAD subjects were classified correctly, independent of the ECG, and with no effect of heart murmurs  

    Validation of the revised stressful life event questionnaire using a hybrid model of genetic algorithm and artificial neural networks

    , Article Computational and Mathematical Methods in Medicine ; Volume 2013 , 2013 ; 1748670X (ISSN) Sali, R ; Roohafza, H ; Sadeghi, M ; Andalib, E ; Shavandi, H ; Sarrafzadegan, N ; Sharif University of Technology
    Objectives. Stressors have a serious role in precipitating mental and somatic disorders and are an interesting subject for many clinical and community-based studies. Hence, the proper and accurate measurement of them is very important. We revised the stressful life event (SLE) questionnaire by adding weights to the events in order to measure and determine a cut point. Methods. A total of 4569 adults aged between 18 and 85 years completed the SLE questionnaire and the general health questionnaire-12 (GHQ-12). A hybrid model of genetic algorithm (GA) and artificial neural networks (ANNs) was applied to extract the relation between the stressful life events (evaluated by a 6-point Likert scale)... 

    Electrochemical determination of clozapine on MWCNTs/new coccine doped ppy modified GCE: An experimental design approach

    , Article Bioelectrochemistry ; Volume 90 , 2013 , Pages 36-43 ; 15675394 (ISSN) Shahrokhian, S ; Kamalzadeh, Z ; Hamzehloei, A ; Sharif University of Technology
    The electrooxidation of clozapine (CLZ) was studied on the surface of a glassy carbon electrode (GCE) modified with a thin film of multiwalled carbon nanotubes (MWCNTs)/new coccine (NC) doped polypyrrole (PPY) by using linear sweep voltammetry (LSV). The pH of the supporting electrolyte (D), drop size of the cast MWCNTs suspension (E) and accumulation time of CLZ on the surface of modified electrode (F) was considered as effective experimental factors and the oxidation peak current of CLZ was selected as the response. By using factorial-based response-surface methodology, the optimum values of factors were obtained as 5.44, 10 μL and 300 s for D, E and F respectively. Under the optimized... 

    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
    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... 

    Optimization of dispersive liquid-liquid microextraction and improvement of detection limit of methyl tert-butyl ether in water with the aid of chemometrics

    , Article Journal of Chromatography A ; Volume 1217, Issue 45 , November , 2010 , Pages 7017-7023 ; 00219673 (ISSN) Karimi, M ; Sereshti, H ; Samadi, S ; Parastar, H ; Sharif University of Technology
    Dispersive liquid-liquid microextraction (DLLME) coupled with gas chromatography-mass spectrometry-selective ion monitoring (GC-MS-SIM) was applied to the determination of methyl tert-butyl ether (MTBE) in water samples. The effect of main parameters affecting the extraction efficiency was studied simultaneously. From selected parameters, volume of extraction solvent, volume of dispersive solvent, and salt concentration were optimized by means of experimental design. The statistical parameters of the derived model were R 2=0.9987 and F=17.83. The optimal conditions were 42.0μL for extraction solvent, 0.30mL for disperser solvent and 5% (w/v) for sodium chloride. The calibration linear range... 

    Cuffless blood pressure estimation algorithms for continuous health-care monitoring

    , Article IEEE Transactions on Biomedical Engineering ; Volume 64, Issue 4 , 2017 , Pages 859-869 ; 00189294 (ISSN) Kachuee, M ; Kiani, M. M ; Mohammadzade, H ; Shabany, M ; Sharif University of Technology
    IEEE Computer Society  2017
    Goal: Continuous blood pressure (BP) monitoring can provide invaluable information about individuals' health conditions. However, BP is conventionally measured using inconvenient cuff-based instruments, which prevents continuous BP monitoring. This paper presents an efficient algorithm, based on the pulse arrival time (PAT), for the continuous and cuffless estimation of the systolic BP, diastolic blood pressure (DBP), and mean arterial pressure (MAP) values. Methods: The proposed framework estimates the BP values through processing vital signals and extracting two types of features, which are based on either physiological parameters or whole-based representation of vital signals. Finally,... 

    Computer aided decision making for heart disease detection using hybrid neural network-Genetic algorithm

    , Article Computer Methods and Programs in Biomedicine ; Volume 141 , 2017 , Pages 19-26 ; 01692607 (ISSN) Arabasadi, Z ; Alizadehsani, R ; Roshanzamir, M ; Moosaei, H ; Yarifard, A. A ; Sharif University of Technology
    Elsevier Ireland Ltd  2017
    Cardiovascular disease is one of the most rampant causes of death around the world and was deemed as a major illness in Middle and Old ages. Coronary artery disease, in particular, is a widespread cardiovascular malady entailing high mortality rates. Angiography is, more often than not, regarded as the best method for the diagnosis of coronary artery disease; on the other hand, it is associated with high costs and major side effects. Much research has, therefore, been conducted using machine learning and data mining so as to seek alternative modalities. Accordingly, we herein propose a highly accurate hybrid method for the diagnosis of coronary artery disease. As a matter of fact, the... 

    An expert system for selecting wart treatment method

    , Article Computers in Biology and Medicine ; Volume 81 , 2017 , Pages 167-175 ; 00104825 (ISSN) Khozeimeh, F ; Alizadehsani, R ; Roshanzamir, M ; Khosravi, A ; Layegh, P ; Nahavandi, S ; Sharif University of Technology
    Elsevier Ltd  2017
    As benign tumors, warts are made through the mediation of Human Papillomavirus (HPV) and may grow on all parts of body, especially hands and feet. There are several treatment methods for this illness. However, none of them can heal all patients. Consequently, physicians are looking for more effective and customized treatments for each patient. They are endeavoring to discover which treatments have better impacts on a particular patient. The aim of this study is to identify the appropriate treatment for two common types of warts (plantar and common) and to predict the responses of two of the best methods (immunotherapy and cryotherapy) to the treatment. As an original work, the study was... 

    Automatic segmentation, detection, and diagnosis of abdominal aortic aneurysm (AAA) using convolutional neural networks and hough circles algorithm

    , Article Cardiovascular Engineering and Technology ; Volume 10, Issue 3 , 2019 , Pages 490-499 ; 1869408X (ISSN) Mohammadi, S ; Mohammadi, M ; Dehlaghi, V ; Ahmadi, A ; Sharif University of Technology
    Springer New York LLC  2019
    Purpose: An abdominal aortic aneurysm (AAA) is known as a cardiovascular disease involving localized deformation (swelling or enlargement) of aorta occurring between the renal and iliac arteries. AAA would jeopardize patients’ lives due to its rupturing risk, so prompt recognition and diagnosis of this disorder is vital. Although computed tomography angiography (CTA) is the preferred imaging modality used by radiologist for diagnosing AAA, computed tomography (CT) images can be used too. In the recent decade, there has been several methods suggested by experts in order to find a precise automated way to diagnose AAA without human intervention base on CT and CTA images. Despite great... 

    Application of single-nucleotide polymorphisms in the diagnosis of autism spectrum disorders: a preliminary study with artificial neural networks

    , Article Journal of Molecular Neuroscience ; Volume 68, Issue 4 , 2019 , Pages 515-521 ; 08958696 (ISSN) Ghafouri Fard, S ; Taheri, M ; Omrani, M. D ; Daaee, A ; Mohammad Rahimi, H ; Kazazi, H ; Sharif University of Technology
    Springer New York LLC  2019
    Autism spectrum disorder (ASD) includes different neurodevelopmental disorders characterized by deficits in social communication, and restricted, repetitive patterns of behavior, interests or activities. Based on the importance of early diagnosis for effective therapeutic intervention, several strategies have been employed for detection of the disorder. The artificial neural network (ANN) as a type of machine learning method is a common strategy. In the current study, we extracted genomic data for 487 ASD patients and 455 healthy individuals. All individuals were genotyped in certain single-nucleotide polymorphisms within retinoic acid-related orphan receptor alpha (RORA), gamma-aminobutyric...