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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
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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Publication Date
Tue Jul 01 2025
Journal Name
Journal Of Breast Diseases
Association Between Serum Interleukin-41 Levels and Breast Cancer Status: A Case–Control Study in Iraqi Women
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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
Wed Oct 01 2014
Journal Name
Engineering And Technology Journal
Investigating Forward kinematic Analysis of a 5-axes Robotic Manipulator using Denavit-Hartenberg Method and Artificial Neural Network
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Publication Date
Wed Feb 01 2023
Journal Name
Asian Pacific Journal Of Cancer Prevention
Cytotoxic Activity of the Ethyl Acetate Extract of Iraqi Carica papaya Leaves in Breast and Lung Cancer Cell Lines
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Publication Date
Sun Jan 01 2023
Journal Name
The Egyptian Journal Of Hospital Medicine
High Tumor Levels of Ki-67, VEGF and Endostatin Are Associated with Progression of Breast Cancer in Iraqi Women
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Publication Date
Wed Jun 26 2024
Journal Name
Opera Medica Et Physiologica
The Impact of Global DNA Methylation and Hypoxia-Inducible Factor 1 Alpha Levels in the Progression of Breast Cancer
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Publication Date
Wed Sep 29 2021
Journal Name
Biomass Conversion And Biorefinery
Encapsulated deep eutectic solvent for esterification of free fatty acid
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A novel encapsulated deep eutectic solvent (DES) was introduced for biodiesel production via a two-step process. The DES was encapsulated in medical capsules and were used to reduce the free fatty acid (FFA) content of acidic crude palm oil (ACPO) to the minimum acceptable level (< 1%). The DES was synthesized from methyltriphenylphosphonium bromide (MTPB) and p-toluenesulfonic acid (PTSA). The effects pertaining to different operating conditions such as capsule dosage, reaction time, molar ratio, and reaction temperature were optimized. The FFA content of ACPO was reduced from existing 9.61% to less than 1% under optimum operating conditions. This indicated that encapsulated MTPB-DES performed high catalytic activity in FFA esterificatio

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Publication Date
Wed Oct 05 2011
Journal Name
Iraqi Journal Of Physics
Study of linear shrinkage for siliceous materials to meet insulating requirements
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