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Treatment of Nasopharyngeal Carcinoma by Using Deep X-Ray Therapy
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Background: Nasopharyngeal carcinoma (NPC) is one of the most challenging tumors because of their relative inaccessibility and that their spread can occur without significant symptoms with few signs, but Radiotherapy (RT) has a role in treatment of it.
Objectives: To show that RT is still the modality of choice in the treatment of NPC, to study modes of presentations, commonest histopathological types and their percentages, to show differences in the sensitivities of these types to RT and to find out a 5 year survival rate(5YSR) and its relation with lymph node involvement.
Methods: This is a retrospective study of 44 patients with NPC who were treated with routine RT from 1988-2007 at the institute of radiology and nuclear medicine. All patients were treated with megavoltage x-ray with a total dose to the primary lesion was 60-70 Grays (1 Gray = 100 Rads) so we gave 6000-7000 Rads in 6-8 weeks and 50 Grays were applied to the cervical lymphatic chain bilaterally.
Results: 10 out of 44 patients treated have survived more than 5 years (with a 5YSR of 22.7%). In this series of cases, the 5- year overall survival rate is: 60% with stage I, 33.3% with stage II, 28.5% with stage III and 13.7% with stage IV. But, it should be noted that most of them were advanced with stages III and IV accounting for 36 patients i.e 81.8%.
Conclusion: Radiotherapy (RT) is the modality of choice in the treatment of NPC and we must irradiate areas of probable spread with the primary lesion because spread can occur without significant signs and symptoms .The most common histopathological type is undifferentiated carcinoma which is more sensitive to RT than squamous cell carcinoma (scc) or other types of carcinoma.
Also we see that stages III and IV NPC (advanced) comprises high number of the total and the 5-YSR decreases as the patient advances from stage I to stage IV, therefore, early detection and diagnosis is very important.

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
Deep Reinforcement Learning: Bridging Learning and Control in Intelligent Systems
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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical And Cellular Archives
THE ONCOGENIC EFFECT OF EBV/HPV CO-INFECTION IN A GROUP OF IRAQI WOMEN WITH CERVICAL CARCINOMA
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The current paper was designed to find the possible synergic effect of EBV infection with the HPV-16 in Iraqi women suffering from cervical carcinoma. This retrospective study involved paraffinized blocks of two groups. The research included 30 carcinomatous cervical tissues and 15 samples from normal cervical biopsies. After sectioning using positively charged slides, immunohistochemistry (IHC) was performed to detect anti-Epstein Barr Virus LMP1 and Human papillomavirus type 16 primary antibodies. Sixty-three percentage (19 out of 30) of the studies group showed positive overexpression as shown in with a significant association of the expression with cervical cancer with a significant association (p = 0). The co-infection of the EBV and H

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Tue Aug 01 2017
Journal Name
International Journal Of Advanced Research In Computer And Communication Engineering
Information hiding by using Developed M8PAM Technique
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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Public key system by using isomorphism group
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In this paper we deal with the problem of ciphering and useful from group isomorphism for construct public key cipher system, Where construction 1-EL- Gamal Algorithm. 2- key- exchange Algorithm

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Fuzzy-assignment Model by Using Linguistic Variables
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      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

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Publication Date
Sun Jun 01 2008
Journal Name
Baghdad Science Journal
The Writer Authentication by Using Syllables Frequency
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An approach is depended in the recent years to distinguish any author or writer from other by analyzing his writings or essays. This is done by analyzing the syllables of writings of an author. The syllable is composed of two letters; therefore the words of the writing are fragmented to syllables and extract the most frequency syllables to become trait of that author. The research work depend on analyzed the frequency syllables in two cases, the first, when there is a space between the words, the second, when these spaces are ignored. The results is obtained from a program which scan the syllables in the text file, the performance is best in the first case since the sequence of the selected syllables is higher than the same syllables in

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