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Clinicopathological Features and ICD-10 Categorization of Oro-maxillofacial Surgical Biopsies from Sulaimani
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Background: Few updated retrospective histopathological-based studies in Iraq evaluate a comprehensive spectrum of oro-maxillofacial lesions. Also, there was a need for a systematic way of categorizing the diseases and reporting results in codes according to the WHO classification that helps occupational health professionals in the clinical-epidemiological approach.

Objectives: to establish an electronic archiving database according to the ICD-10 that encompasses oro-maxillofacial lesions in Sulaimani city for the last 12 years, then to study the prevalence trend and correlation with clinicopathological parameters.

Subjects and Methods:  A descriptive-analytical study included the archived records from three major histopathological centers in Sulaimani (College of Dentistry, Shahid Saifaldeen, and Shorsh Hospitals), related to surgical biopsies of oro-maxillofacial lesions performed between 2008 and 2019 in Sulaimani. Data were tabulated in an excel sheet and analyzed.

Results: This study involved 2100 oro-maxillofacial lesions, male: female ratio was  1:1.2, and a mean age of 41.03±19.51 years old. The most frequently involved sites were; the lip (14.5%), followed by the gum and alveolar ridge (14.2%). 69.4% of cases were non-neoplastic lesions. The neoplastic lesions were significantly (P=.000) observed in old patients with a mean age of 46.1±21.09, mostly epithelial tumors (39.1%), followed by connective tissue tumors (19.5%). Malignant connective tissue tumors were more frequently seen than benign ones (52.5% versus 47.5%). The non-neoplastic lesions revealed predominate soft tissue lesions (45.2%), followed by salivary gland diseases (13.8%), with a mean age of 38.26±18.8. Squamous cell carcinoma was the most common epithelial tumor, while haemangioma was predominant among connective tissue tumors

Conclusions: ICD-10 classification of oro-maxillofacial lesions in Sulaimani city helps establish a standardized coding database system for clinicopathological distribution. However, the majority of recorded lesions were non-neoplastic especially diagnosed as soft tissue lesions. Still, neoplastic lesions with their minor distribution deserve great attention as they threaten patients’ lives.

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Features of Historical Approach in Thinking the Grammar In Ibin Ginie: Features of Historical Approach in Thinking the Grammar In Ibin Ginie
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Abstract:
This research to monitor the features of the historical method in the
thought of a linguistic scientist is known (ibin genieD. 392 AH by offering a
range of grammatical rules presented in his book (the properties and the
nature of their treatment on the basis of the historical method in accordance
with These are an important milestone in facilitating the grammatical rules and
display image "makes it more suitable for the social reality

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Publication Date
Wed Dec 08 2021
Journal Name
J. Inf. Hiding Multim. Signal Process.
Predication of Most Significant Features in Medical Image by Utilized CNN and Heatmap.
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The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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Publication Date
Thu Apr 14 2016
Journal Name
Bio--genetics Journal
Correlation of Her-2/neu gene amplification by FISH and CISH with clinicopathological parameter of Iraqi breast carcinoma patients at central public health laboratories
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The objective of the study: is to investigate the correlations between the HER2 neu gene status with the clinicopathological parameters of infiltrative breast carcinoma. A total of seventy four Iraqi breast cancer patients were collected from one center (Department of Public Health) paraffin blocks were collected from histopathology department central public health laboratories, Bagdad, Iraq from 2014-2015. The cases which has been taken included invasive ductal and invasive lobular carcinoma type Women age were ranged from 24-80 years old. Evaluation of Her-2/neu gene amplification status was done using FISH and CISH techniques that showed a significant correlations with clinicopathological parameters.

Publication Date
Fri Jan 01 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Genetic--Based Face Retrieval Using Statistical Features
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Publication Date
Thu Nov 01 2018
Journal Name
2018 1st Annual International Conference On Information And Sciences (aicis)
Speech Emotion Recognition Using Minimum Extracted Features
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Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

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Publication Date
Sun Sep 24 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Human Recognition Using Ear Features: A Review
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Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

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Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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Publication Date
Mon Jan 02 2017
Journal Name
Al-academy
Features tendency cosmic in contemporary Iraqi configuration
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The research current ( features tendency cosmic in contemporary Iraqi configuration) attempt to study the dimensions of the conceptual and philosophical foundations upon which the tendency of cosmic within the period that extended its influence beyond the place where I grew up to be circulated concepts in all parts of the world, it is no doubt that the world is now heading to rapprochement after the tremendous developments in the field of communication technology and reflected heavily on identity concepts, privacy, the concept of nation-states ... etc. to become an individual and a large area of access to other cultures, and all that aroused the interest of contemporary Iraqi artist this interest arising from the desire to keep up with d

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Publication Date
Mon Mar 23 2020
Journal Name
Baghdad Science Journal
Molecular Modeling and in Silico Characterization of a Pathogenesis-Related Protein-10 (PR10) and its Coding Genes in some Oryza Species
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Rice is a major staple food for more than two thirds of the world population. Pathogenesis-related proteins-10 (PR10) have a range of 154 to 163 amino acid with molecular weight ~ 17 kDa.  They are acidic and generally intracellular and cytosolic proteins accumulate in plants in response to biotic and abiotic stresses. In the present study, a PR10 gene and its corresponding protein were characterized in O. sativa, O.  barthii, O. glaberrima, O. glumipatula, O. meridionalis, O. nivara, O. rufipogon and  O. punctata. The results revealed a narrow range of variation at both DNA and protein levels in all examined species except O. glumipatula. The latter showed a relatively

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