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The influence of Breast Cancer Molecular Subtypes on Metastatic pattern in Iraqi patients

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Publication Date
Mon Aug 26 2019
Journal Name
Iraqi Journal Of Science
Study on lung infections of patients with cancer under chemotherapy

The aim of this study is to assess the prevalence of lung infections among a group of hospitalized cancer patients who received chemotherapy as well as to describe a population of these patients. The clinical data and demographic information were collected from the archived files of  in-patients  referred to  hematology center  / Baghdad Teaching Hospital / Medical City , ministry of health, Iraq  during the period  of  2018.

    This study was carried out on 250 patients with different types of cancer ,they were mostly of age group (40 - 49)  59 / 250 (23.6)% , (14-19) 49 /250 (19.6%) and (60-69) 41/ 250(16.4%) . The patients had two major types of hematological malignancies

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Detection of Anti-cancer Activity of Silver Nanoparticles Synthesized using Aqueous Mushroom Extract of Pleurotus ostreatus on MCF-7 Human Breast Cancer Cell Line

     In this research, silver nanoparticles (AgNPs) were manufactured using aqueous extract of mushroom Pleurotus ostreatus. Anticancer potential of AgNPs was investigated versus human breast cancer cell line (MCF-7). Cytotoxic response was assessed by MTT assay. AgNPs showed inhibition effect at the following concentrations 12.5, 25, 50, 100 and 200 µg/ml versus MCF-7 cell line, and all treatments had a positive result. The MCF-7 cells were inhibited up to 85.14 % at the concentration 200 μg/ml of AgNPs which reduced cells viability to 14.86%, while 12.5 μg/ml of AgNPs caused 24.23% cells inhibition with reduction of cells viability to 75.77%.

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis

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

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Publication Date
Tue Sep 01 2020
Journal Name
Clinical Plasma Medicine
Breast cancer treatment using cold atmospheric plasma generated by the FE-DBD scheme

Background Cold atmospheric plasma (CAP) is widely used in the cancer therapy field. This type of plasma is very close to room temperature. This paper illustrates the effects of CAP on breast cancer tissues both in vivo and in vitro. Methods The mouse mammary adenocarcinoma cell line AN3 was used for the in vivo study, and the MCF7, AMJ13, AMN3, and HBL cell lines were used for the in vitro study. A floating electrode-dielectric barrier discharge (FE-DBD) system was used. The cold plasma produced by the device was tested against breast cancer cells. Results The induced cytotoxicity percentages were 61.7%, 68% and 58.07% for the MCF7, AMN3, and AMJ13 cell lines, respectively, whereas the normal breast tissue HBL cell line exhibited very li

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Publication Date
Mon Jan 01 2024
Journal Name
Malaysian Journal Of Nursing
Experiences of Nurses in Providing Care for Patients on the Cancer Journey: A Cross-Sectional Survey

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Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Best Way to Detect Breast Cancer by UsingMachine Learning Algorithms

Breast cancer is the second deadliest disease infected women worldwide. For this
reason the early detection is one of the most essential stop to overcomeit dependingon
automatic devices like artificial intelligent. Medical applications of machine learning
algorithmsare mostly based on their ability to handle classification problems,
including classifications of illnesses or to estimate prognosis. Before machine
learningis applied for diagnosis, it must be trained first. The research methodology
which isdetermines differentofmachine learning algorithms,such as Random tree,
ID3, CART, SMO, C4.5 and Naive Bayesto finds the best training algorithm result.
The contribution of this research is test the data set with mis

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Publication Date
Mon Jan 30 2023
Journal Name
Iraqi Journal Of Science
Cytotoxic Effect of the Alcoholic Extract of Conocarpus erectus Leaves on MDA-MB 231 and MCF7 Breast Cancer Cell Lines

    Currently, there is a growing interest in medicinal plants extracts as some plants have shown antitumor potential. The goal of this study was to test the anticancer activity of methanol extract of Conocarpous erectus leaves in breast cancer cells.  Cytotoxicity was tested in vitro on breast cancer cell lines, MCF7 [Estrogen receptor + (ER+)] and MDA-MB231 [Estrogen receptor - (ER-)], in addition to normal fibroblast cells (REF). MTT assay was utilized to measure the growth inhibitory effects after 48 hours exposure to extracts.  Viability results indicated  that MDA-MB231 were sensitive (GI50 = 56.1µg/ml).However, no sensitivity was seen in both MCF7 and REF cells (GI50>100 µg/ml). I

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Advanced Pharmaceutical Technology & Research
Exploring the modulation of MLH1 and MSH2 gene expression in hesperetin-treated breast cancer cells (BT-474)
A<sc>BSTRACT</sc> <p>The major mortality factor for women globally is breast cancer, and current treatments have several adverse effects. Hesperetin (HSP) is a flavone that occurs naturally with anti-tumor capabilities and has been investigated as a potential treatment for cancer. This study aimed to investigate the cytotoxic and anti-malignant potential of HSP on breast cancer cells (BT-474) and normal cells (MCF-10a). The results indicated that HSP has dose-dependent cytotoxicity in BT-474 and MCF-10a cells. The elevated concentration of HSP lowered cell viability and proliferation. The half-maximal inhibitory concentration (IC<sub>50</sub>) of HSP in BT-</p> ... Show More
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Publication Date
Fri Jan 01 2016
Journal Name
Al–bahith Al–a'alami
The Influence of Turkish Soap Operas in the Behavior and Trends of the Iraqi Audience (A Field Study on Iraqi University's Students)

This research seeks the effects of dubbed Turkish TV series on Iraqi audiences. The chosen sample is about 600 Iraqi students at Baghdad and al-Anbar Universities. This study consists of four sections: section one deals with the theoretical framework of the study. Section two studies the dubbed Turkish TV series. The third section explores the role of mass media in forming tendencies, and the last section seeks the field study by analyzing the tendencies if Iraqi viewers of these series.
The goal of this study is to know the role these series played in affecting the behavior and attitudes of Iraqi people and how it can change their morals.
The research ends with the number of results like the negative effect of these series on the

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Crossref
Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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