Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using

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

This study was designed to monitor the ambient air pollution in several sites within Baghdad City of Iraq. The readings started from May 2016 to April 2017. The highest concentration of sulfur dioxide (SO2) was 2.28 ppmm-3 while nitrogen dioxide (NO2) was 3.68 ppmm-3 and suspended particulate matter was 585.1 ?gm-3. This study also included estimating the value of the air pollution tolerance index (APTI) for four plant's species Olea europaea L., Ziziphus spina-Christi (L.) Desf, Albizia lebbeck(L.) Benth. and Eucalyptus camaldulensis Dehnh. Were cultivated on the road sides. The study includes four biochemical parameters, total chlorophyll content, ascorbic acid content, pH and relative water content of plant leaves. The results show that

 We conclude that this study has dealt with an important aspect of the book that was not clearly defined in the book as it was derived through the book's translations, namely, the extraction of those urban structures of the city of Baghdad, which were of great importance in the religious, cultural, economic and social life at that time, The important link that reflected the development of the Islamic city in general and Baghdad in particular, as he addressed such urban facilities through the translations of the book that did not offer the outline or information about those facilities, but only the name only, and here lies the difficulty in addressing Such as T. As subjects because they need the most accurate analysis of facilities t

The utilization of targeted therapy for programmed death ligand 1 (PD‑L1) has emerged as a prominent focus in contemporary clinical trials, particularly in the context of immune checkpoint inhibitors. The prognostic significance of the expression of PD‑L1 in invasive mammary cancer remains a subject of discussion in clinical oncology, requiring further exploration, despite its recognition as a biomarker for responsiveness to anti‑PDL1 immunotherapy. The present study was conducted to investigate the immunohistological expression of PD‑L1 in women with triple‑negative breast cancer (TNBC), with a particular focus for searching for the associated clinical and pathological characteristics. The present retrospective study examined the

Breast cancer (BC) is first of the top 10 malignancies in Iraq. Dose‐volume histograms (DVHs) are most commonly used as a plan evaluation tool. This study aimed to assess DVH statistics using three‐dimensional conformal radiotherapies in BC in an adjuvant setting.

The mobile phone is widespread all over the world. This technology is one of the most widespread with more than five billion subscriptions making people describe this interaction system as Wireless Intelligence. Mobile phone networks become the focus of attention of researchers, organizations and governments due to its penetration in all life fields. Analyzing mobile phone traces allows describing human mobility with accuracy as never done before. The main objective in this contribution is to represent the people density in specific regions at specific duration of time according to raw data (mobile phone traces). This type of spatio-temporal data named CDR (Call Data Records), which have properties of the time and spatial indications for th

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope