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Cutaneous leishmaniasis: Comparative Techniques for Diagnosis
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AR Al-Heany BSc, PKESMD MSc., PSAANBS PhD, APAANMD MSc., DDV, FICMS., IOSR Journal of Dental and Medical Sciences (IOSR-JDMS), 2014 - Cited by 14

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Publication Date
Fri Oct 14 2022
Journal Name
Diagnostics
Determination of the Accuracy of Salivary Biomarkers for Periodontal Diagnosis
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Background: We aimed to investigate the accuracy of salivary matrix metalloproteinases (MMP)-8 and -9, and tissue inhibitor of metalloproteinase (TIMP)-1 in diagnosing periodontitis and in distinguishing periodontitis stages (S)1 to S3. Methods: This study was a case–control study that included patients with periodontitis S1 to S3 and subjects with healthy periodontia (controls). Saliva was collected, and then, clinical parameters were recorded, including plaque index, bleeding on probing, probing pocket depth, and clinical attachment level. Diagnosis was confirmed by assessing the alveolar bone level using radiography. Salivary biomarkers were assayed using an enzyme-linked immunosorbent assay. Results: A total of 45 patients (15

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Publication Date
Sat Jan 04 2020
Journal Name
Nternational Journal Of Plasma Environmental Science And Technology (ijpest)
Use of cold plasma in the synthesis of gold nanomaterials for parasitic leishmaniasis treatment
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The atmospheric air cold plasma has been used to manufacture gold nanomaterials for treating parasitic leishmaniasis. This study experimentally assessed the treatment of Leishmania parasites (L. donovani and L. tropica) by gold nanoparticles. Specifically, atmospheric pressure nonthermal plasma was generated using different diameters (1.0, 2.8, 3.8 and 4.3 mm) of high voltage electrode. Aqueous gold tetrachloride salts (HAuCl4·4H2O) were used as precursor to produce gold nanoparticles. UV-vis spectroscopy and x-ray diffraction were conducted for characterization of the nanoparticles. The optimum condition (a diameter of 1 mm) was chosen to prepare gold nanoparticles, where the grain size was found to be 17 nm. Accordingly, the nanoparticle

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Publication Date
Wed Dec 30 2020
Journal Name
Al-kindy College Medical Journal
Comparative Study between Nasal Endoscopic Findings and Nose and Paranasal Sinus Computerized Tomography in diagnosis of Nose and Paranasal Sinuses Diseases
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Background: Nasal obstruction is common in otorhinolaryngology outpatient visitors. The diagnosis of such compliant is by history, clinical examination and diagnostic procedures. Nasal endoscopy and computerized tomography scan are common diagnostic investigations. Nasal obstruction is either anterior or posterior (nasal septal deviations, hypertrophied turbinate pathological cyst, polyps, mass etc), or postnasal obstruction (hypertrophied turbinate, adenoid hypertrophy, nasopharyngeal cyst or nasopharyngeal tumors).

Aim of study: Prospective study to compare endoscopic finding and computerized tomography of nose, paranasal sinuses and postnasal space as diagnostic methods for nasal obstruction and other nose, p

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Publication Date
Fri Jul 24 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Fracture strength of laminate veneers using different restorative materials and techniques (A comparative in vitro stuy)
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Background: Esthetic correction represents one of the clinical conditions that required the use of laminate veneers in premolars region. Aim of the study: The purpose of this study was to evaluate the fracture strength of the laminate veneers in maxillary first premolars, fabricated from either composite (direct and indirect techniques) or ceramic CAD/CAM blocks. Materials and Methods: Fifty sound human maxillary premolar teeth were used in this in vitro study. Teeth were divided randomly into one control group and four experimental groups of ten teeth each; Group A: Restored with direct composite veneer (Filtek Z250 XT), Group B: Restored with indirect composite veneers (Filtek Z250 XT), Group C: Restored with lithium disilicate ceramic CA

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Thu Sep 12 2019
Journal Name
Al-kindy College Medical Journal
Assessment of stromal eosinophilia in cutaneous squamous cell carcinoma
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Background: Tumor associated tissue eosinophilia (TATE) has been described in a variety of neoplasms. In regard to squamous cell carcinoma, some studies worldwide done to assess stromal eosinophilia in oral and cervical squamous cell carcinoma. The objectives of this study is to evaluate the association of stromal eosinophilic infiltration of cutaneous squamous cell carcinoma and to detect the significance of this association. Aim of the study The aim of our study is to establish the relationship between the degree of stromal eosinophilia and the level of invasion and the histological grade in cutaneous squamous cell carcinoma. Methods: In this retrospective study done at the histopathology department of al Wasity teaching hospital for orth

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Publication Date
Thu Sep 12 2019
Journal Name
Al-kindy College Medical Journal
Assessment of stromal eosinophilia in cutaneous squamous cell carcinoma
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Background: Tumor associated tissue eosinophilia (TATE) has been described in a variety of neoplasms. In regard to squamous cell carcinoma, some studies worldwide done to assess stromal eosinophilia in oral and cervical squamous cell carcinoma. The objectives of this study is to evaluate the association of stromal eosinophilic infiltration of cutaneous squamous cell carcinoma and to detect the significance of this association.

Aim of the study

The aim of our study is to establish the relationship between the degree of stromal eosinophilia and the level of invasion and the histological grade in cutaneous squamous cell carcinoma.

Methods: In this retrospective study

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Publication Date
Sun Mar 13 2011
Journal Name
Baghdad Science Journal
Antibody response in Hamsters Immunized against experimental Leishmaniasis
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Direct agglutination test was used to evaluate the immunogenicity of three different antigens inoculated in hamsters as one , two and three doses which were: Group (1) inoculated with autoclaved killed Leishmania tropica , Group (2) inoculated with BCG vaccine alone while Group (3) inoculated with mixed antigens (autoclaved killed Leishmania "AKL"+ BCG).(4) Control animals inoculated with phosphate buffer saline. The maximum level of antibody titers were evaluated in animal inoculated with one , two or three dose of mixed antigens (320 , 640 and 1280) respectively when it compared with animals inoculated with corresponding doses of AKL antigen (80 , 160 and 320) respectively. While the minimum level of antibody titers were observed in ani

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Mon Jun 01 2009
Journal Name
2009 Etp International Conference On Future Computer And Communication
Signal Processing Techniques for Robust Spectrum Sensing
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Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper ,

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