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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 on each subsystem to futher reduce the hardware requirements. The DNN was designed using a system generator and implemented using very hardware description language (VHDL). The system achievments outcomes the superior’s accuracy rate of approximately 99.6 percent in distinguishing bengin from malignant tissue. Also, the hardware resources were reduced by 30 percent from works of literature with an error rate of 7e-4 when using the Kintex-7 xc7k325t-3fbg676 board.

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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
Social Support and Its Relationship to Psychological Rigidity in a Sample of Breast Cancer Patients In the Ramallah and Al-Bireh Governorate
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This study aims to identify the impact of social support on breast cancer patients’ psychological rigidity using a sample in Ramallah and al-Bireh. A descriptive correlative approach was adopted to fulfill the goals of the study and a questionnaire consisted of two criteria: social support and psychological rigidity, which was adopted as a tool for data collection for the study. In order to achieve the goals of the study, the researcher selected a convenient sample that consisted of 123 female breast cancer patients in Ramallah and al-Bireh. This sample represented 50% of the original patient population. The study showed that the average estimated percentage of social support and psychological rigidity for women with breast cancer, in

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Banking Entrepreneurial requirements: Models for selected countries: Models for selected countries
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The research aims to identify the requirements of banking Entrepreneurial in Saudi Arabia and Singapore, where banking Entrepreneurial is an important way to lead employees to acquire the experience and knowledge required by the banking environment, so we note the pursuit of the banking management to acquire new technology proactively and distinctively to compete with others through the introduction of modern technologies that help senior management to develop new banking methods adaptable to the surrounding environmental changes. The problem of research highlights the extent to which the requirements of banking Entrepreneurial are applied in Saudi Arabia and the Republic of Singapore and will be addressed through three investigation

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Publication Date
Sat Mar 01 2025
Journal Name
Iraqi Journal Of Physics
Design an Efficient Neural Network to Determine the Rate of Contamination in the Tigris River in Baghdad City
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This article proposes a new technique for determining the rate of contamination. First, a generative adversarial neural network (ANN) parallel processing technique is constructed and trained using real and secret images. Then, after the model is stabilized, the real image is passed to the generator. Finally, the generator creates an image that is visually similar to the secret image, thus achieving the same effect as the secret image transmission. Experimental results show that this technique has a good effect on the security of secret information transmission and increases the capacity of information hiding. The metric signal of noise, a structural similarity index measure, was used to determine the success of colour image-hiding t

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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Sun Jul 01 2018
Journal Name
Saudi Medical Journal
Serum anti-müllerian hormone levels in evaluation of chemotherapy effect on ovarian reserve in women with breast cancer
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Publication Date
Wed Feb 01 2023
Journal Name
Eurasian Chemical Communications
Assessment of systemic oxidative stress and antioxidants in Iraqi women with newly diagnosed and tamoxifen-treated breast cancer
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Breast cancer (BC) is one of the most frequently observed malignancy in females worldwide. Today, tamoxifen (TAM) is considered as the highly effective therapy for treatment of breast tumors. Oxidative stress has implicated strongly in the pathophysiology of malignancies. This study aimed to investigate the changes in the levels of oxidants and antioxidants in patients with newly diagnosed and TAM-treated BC. Sixty newly diagnosed and 60 TAM-treated women with BC and 50 healthy volunteers were included in this study. Parameters including total oxidant capacity (TOC), total antioxidant capacity (TAC), and catalase (CAT) activity were determined before and after treatment with TAM. The serum levels of TOC and oxidative stress index (OSI) were

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Preliminary study of the insulin growth factor binding protein-3 (IGFBP3) level in Iraqi women with breast cancer
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Here, a high sensitive method for biomarker identification according to nanostructure, using enzyme-linked immunosorbent assays (ELISAs), called Nano-ELISA, was presented. Different shapes of gold nanostructures (star and sphere; GNSs and GNPs) with a particle size of 40 nm for sphere particles were altered with a monoclonal antibody (Ab) as a detector Ab. To amplify the optical signal, gold nanostructures were employed as carriers of the signaling specific antibody against insulin growth factor binding protein- 3 (IGFBP-3). The substrate was catalytically oxidized by the Horseradish Peroxidase (HRP) conjugated gold nanostructure, and HRP also enhanced the optical signals, reflecting the amount of the targeting IGFBP-3. In comparison to t

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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
Topical Diclofenac Therapy for Mondor's Disease of the Breast
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Background: Mondor's disease means superficial thrombophlibitis of the chest wall in human, treatment is entirely symptomatic. Hot, wet dressing and anodynes may be used for pain relief.
Objective: To evaluate the role of systemic and transdermal action of diclofenac (olfen) with respect to the symptom and sign (pain, erythema along the superficial vein), and the use of Doppler ultrasonography which is a colored ultrasound used for assessment of flow of blood in vessels.
Method: The study was performed on 12 cases with Mondor's disease in middle age female patients with the involvement of lnframammary veins in all of the them (commonly affected), 4 cases had reassurance only, 4 cases had reassurance with systemic diclofenac, and th

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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 Aug 01 2017
Journal Name
Iosr Journal Of Dental And Medical Sciences (iosr-jdms)
Utilizing Home Pregnancy Test Kits for Diagnosis of Leaking Liquor
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Before the start of delivery, any membranes rupture could be named as a premature rupture of membranes (PROM), which may need special obstetrical interactions to minimize perinatal complications, it is important topromptly diagnose PROM, the method used should be accurate, cheap, simple, and widely available. This was exactly the idea behind this study to use an ordinary pregnancy test kit aiming to confirm presence of PROM.Over a 6 months’ period, 60 pregnant women with a history of leaking liquor and a positive speculum examination for amniotic fluid pooling were collected prospectively and compared with other 60 women (control group) with uneventful pregnancy. Majority of patients with positive leaking liquor signs and symptoms had a p

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