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

Breast cancer (BC) is the most prevalent tract cancer in the world, including Iraq. The classified breast tumors to benign, malignant, and radiotherapy. Cancer treatment depends on certain stages such as mastectomy then chemotherapy alone or with radiation therapy or endocrine therapy according to the prognostic features obtained from the pathology report. The present study included 100 females. The women were split into two groups, control group that consisted of 50 apparently healthy females and 50 patients with BC group who undergo the radiotherapy. The current study highlighted on some of the anthropometric measurements, including the oxidative stress index malondialdehyde (MDA), the concentrations of total antioxidant capacity (TAC), s

The study involved 120 women, who were distributed into two groups of breast tumor patients (30 malignant and 30 benign) and a group of controls (60 women). The patients were referred to the Center for Early Detection of Breast Tumor at Al-Alwayia Hospital for Gynecology and Obstetrics (Baghdad) during the period June-December 2011. They were investigated for the frequency of ABO blood group phenotypes, menopausal status, oral contraceptive use, body mass index and family history of breast cancer or other cancers. The results demonstrated that 60.0% of malignant cases clustered after the age 50 years, while it was 20.0% in benign cases. Fifty percent of malignant breast tumor patients reached menopause, while in benign cases, the corresp

       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.

Neuron-derived neurotrophic factor [NENF], a human plasma neurotrophic factor, also increases neurotrophic activity in conjunction with Parkinson's disease-related proteins in Neudesin. Although Neudesin (neuron-derived neurotrophic secreted protein) is a member of the membrane-associated progesterone receptor (MAPR) protein subclass, it is not evolutionary related to the other members of the same family. The expression of Neudesin is found in both brain and spinal cord from embryonic stages to adulthood, as w Neudesin levels in Parkinson's patients with osteoporosis disease and Parkinson's patients without osteoporosis disease, as well as the relationship between Neudesin levels, Anthropometric and Clinical Features (Age, Gender, BMI) and

Background: although breast cancer in young women is less common and often overlooked, it is still considered a major health concern.
Objectives: to evaluate the demographic, clinical, radiological and histopathological characteristics of breast cancer among a sample of Iraqi women diagnosed under the age of 40 years.
Patients and methods: a retrospective study enrolled 73 females below the age of 40 years with a history of breast cancer. All data was extracted from an established information system database designed by the Principal Investigator of the Iraqi National Breast Cancer Research Project under supervision of the International Agency for Research on Cancer (IARC) over a 4-years period from 2011 to 2014.
Results: sevent

Background: although breast cancer in young women is less common and often overlooked, it is still considered a major health concern.
Objectives: to evaluate the demographic, clinical, radiological and histopathological characteristics of breast cancer among a sample of Iraqi women diagnosed under the age of 40 years.
Patients and methods: a retrospective study enrolled 73 females below the age of 40 years with a history of breast cancer. All data was extracted from an established information system database designed by the Principal Investigator of the Iraqi National Breast Cancer Research Project under supervision of the International Agency for Research on Cancer (IARC) over a 4-years period from 2011 to

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