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Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum error rate, and the test maximum accuracy for K_value selection with an accuracy of 86.24%. Where the distance metric has been assigned using the Euclidean approach. From previous models, it seems that Breast Cancer Grade2 is the most prevalent type. For the future perspective, a comparative study could be performed to compare the supervised and unsupervised data mining algorithms.

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Publication Date
Fri Dec 01 2023
Journal Name
Experimental And Applied Biomedical Research (eabr)
Correlation Between Ultrasound BI-Rads 4 Breast Lesions and Fine Needle Cytology Categories in a Sample of Iraqi Female Patients
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Breast cancer is the most common malignancy in female and the most registered cause of women’s mortality worldwide. BI-RADS 4 breast lesions are associated with an exceptionally high rate of benign breast pathology and breast cancer, so BI-RADS 4 is subdivided into 4A, 4B and 4C to standardize the risk estimation of breast lesions. The aim of the study: to evaluate the correlation between BI-RADS 4 subdivisions 4A, 4B & 4C and the categories of reporting FNA cytology results. A case series study was conducted in the Oncology Teaching Hospital in Baghdad from September 2018 to September 2019. Included patients had suspicious breast findings and given BI-RADS 4 (4A, 4B, or 4C) in the radiological report accordingly. Fine needle aspirati

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Publication Date
Mon Nov 02 2020
Journal Name
International Journal Of Pharmaceutical Research
Extraction, Purification of Alkaloid Compounds from Anastatica Hierochuntica and Studying its Effect on Liver Cancer Cells
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Publication Date
Thu Dec 10 2020
Journal Name
International Journal Of Pharmaceutical Research
Extraction, Purification of Alkaloid Compounds from Anastatica Hierochuntica and Studying its Effect on Liver Cancer Cells
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The current study included the separation of three alkaloid compounds from Anastatica Hierochuntica and studied the effect of the these compounds on cancerous cells , specifically liver cancer it was found that compound number one is the most influential or inhibiting at 50 percent followed by compound number three when using concentration of 400 μg/mL.

Publication Date
Wed Jan 04 2023
Journal Name
Radiochimica Acta
Verification of radon, radium, polonium concentrations and lung cancer rates in blood of female hookah smokers
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Abstract<p>Hookah smoking has become very popular in Iraq among women and men. Hookah tobacco contains natural radioactive elements, such as radon, radium, and uranium, as well as toxic elements, such as polonium, which are released during the combustion of tobacco and are inhaled by smoking. Most reviews focus on hookah tobacco, and only a few have investigated the blood of hookah smokers. In this study, a CR-39 detector was used to measure radon, radium, and polonium concentrations and conduct risk assessments in female hookah smokers of different ages. The results show that the concentrations of radon-222, polonium-218, and polonium-214 varied between 61.62 and 384.80, 5.45–33.64 on the wal</p> ... Show More
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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of Biology And Life Science
Newcastle Disease Virus (NDV) Iraqi Strain AD2141 Induces DNA Damage and FasL in Cancer Cell Lines
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The oncolytic viruses are promising form of cancer therapy which is based on the selectively killing of the cancer cells. This study was aimed to investigate the role of Newcastle disease virus (NDV) Iraqi strain AD2141 in apoptosis. Firstly, the virulence of AD2141 was detected in embryonated chicken eggs after 48hrs of infection. It was observed a hemorrhage in the skin of infected embryos that led to death. Then, the ability of this strain for regression cancer cell lines was examined. By using cytotoxicity test, it was found 128 HAU/ml of AD2141 had a potent inhibition against growth of RD and AMN3 after 72hrs of exposure time; the inhibition rate was 86.8% and 86.98% respectively. Moreover, the apoptotic activity of AD2141 was exami

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Publication Date
Mon Jun 09 2025
Journal Name
Intelligent Decision Technologies
Safety assessment model for DoS attacks detection in wireless communication and network OS environments
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Wireless networks and communications have witnessed tremendous development and growth in recent periods and up until now, as there is a group of diverse networks such as the well-known wireless communication networks and others that are not linked to an infrastructure such as telephone networks, sensors and wireless networks, especially in important applications that work to send and receive important data and information in relatively unsafe environments, cybersecurity technologies pose an important challenge in protecting unsafe networks in terms of their impact on reducing crime. Detecting hacking in electronic networks and penetration testing. Therefore, these environments must be monitored and protected from hacking and malicio

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Publication Date
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
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Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Crossref (5)
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Publication Date
Fri Jun 10 2022
Journal Name
Eurasian Chemical Communications
Detection of lead and cadmium in types of chips from local markets in Baghdad
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Publication Date
Thu Jan 01 2015
Journal Name
Iraqi Journal Of Biotechnology
Detection of E. coli and rotavirus in diarrhea among children under five years old‏
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