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Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that the
proposedmethod obtained very good results but it requires more testing on different types of Skin
Cancer Images.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Thu Apr 20 2023
Journal Name
Fire
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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Publication Date
Mon Jan 01 2018
Journal Name
مجلة مداد الاداب الجامعة العراقية
صورة الولايات المتحدة الأمريكية لدى طلبة الجامعات العراقية دراسة مسحية
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اصبح مصطلح الصورة الذهنية من المصطلحات الشائعة التي يتزايد استخدامها في المجالات السياسية والإعلامية والعلاقات الدولية اذ اصبح يشكل اهمية كبرى لدى دراسي السلوك الانساني، فقد احتلت دراسة المصادر المتعددة التي يستقي منها الافراد انطباعاتهم عن الاخرين، وتعاظم الدور الذي تلعبه وسائل الاتصال في تدفق الصور عن الشعوب في ظل التطور التكنولوجي الهائل الذي يشهده عالم الاتصال حاليا، والذي يسمى بعصر السموات المفتوحة

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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
EFFICIENCY SPIHT IN COMPRESSION AND QUALITY OF IMAGE
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Image compression is an important tool to reduce the bandwidth and storage
requirements of practical image systems. To reduce the increasing demand of storage
space and transmission time compression techniques are the need of the day. Discrete
time wavelet transforms based image codec using Set Partitioning In Hierarchical
Trees (SPIHT) is implemented in this paper. Mean Square Error (MSE), Peak Signal
to Noise Ratio (PSNR) and Maximum Difference (MD) are used to measure the
picture quality of reconstructed image. MSE and PSNR are the most common picture
quality measures. Different kinds of test images are assessed in this work with
different compression ratios. The results show the high efficiency of SPIHT algori

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Information Engineering And Applications
Development of Prognosis Factors in a Scoring System for Predicting of Breast Cancer Mortality
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Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate

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Publication Date
Sat Sep 21 2024
Journal Name
Asian Pacific Journal Of Cancer Prevention
Oncolytic Newcastle Disease Virus and Photodynamic Therapy as Dual Approach for Breast Cancer Treatment
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Objective: We hypothesized that attacking cancer cells by combining various modes of action can hinder them from taking the chance to evolve resistance to treatment. Incorporation of photodynamic therapy (PDT) with oncolytic virotherapy might be a promising dual approach to cancer treatment. Methods: NDV AMHA1 strain as virotherapy in integration with aminolaevulinic acid (ALA) using low power He-Ne laser as PDT in the existing work was examined against breast cancer cells derived from Iraqi cancer patients named (AMJ13). This combination was evaluated using Chou–Talalay analysis. Results: The results showed an increased killing rate when using both 0.01 and 0.1 Multiplicity of infection (MOI) of the virus when combined with a dose of 617

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Publication Date
Wed May 22 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Assessment of Urine and Serum Exosomes as Biomarkers for the Diagnosis of Bladder Cancer
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Background: Bladder cancer (BC) is the most common malignant tumor in the urinary tract and the tenth most common malignancy worldwide. Exosomes are 40–100 nm-diameter nanovesicles that are either released straight from the plasma membrane during budding or merged with the plasma membrane by multivesicular bodies. Objectives: To assess the proportion of serum and urinary Exosome levels in urinary bladder cancer patients, as well as their impact on the disease. Methods: From January 2023 to June 2023, a total of 45 samples of blood and urine were collected from individuals diagnosed with bladder cancer at the Ghazi Hariri Hospital for Specialized Surgery. They included 45 male and female patients, varying in age, as well as 45 heal

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Publication Date
Thu Dec 09 2021
Journal Name
Revista Latinoamericana De Hipertension
Synthesis, chemical hydrolysis and biological evaluation of doxorubicin carbamate derivatives for targeting cancer cell
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Publication Date
Tue Feb 01 2022
Journal Name
Macromolecular Symposia
Synthesis of 5‐Fluorouracil–Naproxen Conjugates as a Mutual Prodrug for Targeting Cancer Tissues
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Abstract<p>A new 5‐fluorouracil–naproxen conjugate is synthesized as a mutual prodrug for targeting cancer tissues. The structure of the target compound and their intermediate are characterized by their melting point, IR, <sup>1</sup>H NMR, <sup>13</sup>C NMR, and elemental microanalysis. The cytotoxic activity is preliminarily evaluated using nonsmall lung cancer CRL‐2049, human breast cancer CAL‐51, and one type of normal cell line; rat embryo fibroblast cell line. The synthesized compound shows a good cytotoxic effect at the cancer cell and no significant effect at rat embryo fibroblast cell line.</p>
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