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 a training data rather than cross validation. The decision tree algorithm J48 is applied to detect and generate the pattern of attributes, which have the real effect on the class value. Furthermore, the experiments are performed with three machine learning algorithms J48 decision tree, simple logistic, and multilayer perceptron using 10-folds cross validation as a test option, and the percentage of correctly classified instances as a measure to determine the best one from them. As well as, this investigation used the iteration control to check the accuracy gained from the three mentioned above algorithms. Hence, it explores whether the error ratio is decreasing after several iterations of algorithm execution or not. Conclusion It is noticed that the error ratio of classified instances are decreasing after 5-10 iterations, exactly in the case of multilayer perceptron algorithm rather than simple logistic, and decision tree algorithms. This study realized that the TPS_pre is the most common effective attribute among three main classes of examined dataset. This attribute highly indicates the BC inflammation.
The current research is concerned with studying the decisive answers which are considered quick and conclusive. These answers can effectively interrupt the opponent's argument and close the dialogue.This research is concentrated on deliberative methodology focusing on the decisive answer's activity and ending them through several completing and argument sides. This research consists of an introduction and three parts, the current introduction is focused the light on the concept of decisive answers and its uses in literature and the scarce of speech, and how to consider it with one dialogue description,that dialogue constitute by ? The first part is concerned with those answers through the deliberative methodology and classifying decisive
... Show MoreObjectives: To assess the relation between breast cancer & blood groups, identify the importance of women
age group and the relation of age with breast cancer.
Methodology: The study was performed on (115) women who were diagnosed with breast cancer in different
stages of disease and different ages. Blood samples were taken from them to demonstrate their blood groups and
(20) fresh tumor tissue samples were obtained; the tumor tissue used as a source of lectin for hemagglutinate
with erythrocyte of different blood groups. The study conducted at Baghdad Teaching Hospital and Radiation &
Nuclear Medicine Hospital from January, 2007 through June 2007.
Results: The study shows that the highest percentage of women
The emergence of staphylococci, either coagulase negative (CNS) or coagulase positive (CPS), as important human pathogens has implied that reliable methods for their identification are of large significance in understanding the diseases caused by them. The identification and characterization of staphylococci from biopsies taken from human breast tumors is reported here. Out of 32 tissue biopsies, a total of 12 suspected staphylococci grew on mannitol salt agar (MSA) medium, including 7 fermenters and 5 non-fermenter staphylococci based on traditional laboratory methods. Polymerase chain reaction (PCR) successfully identified seven isolates at the genus level as methicillin resistant St
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreIn this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for
... Show MoreWisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.
Breast cancer is the most repeatedly detected cancer category and the second reason cause of cancer-linked deaths among women worldwide. Tumor bio-indictor is a term utilized to describe possible indicators for carcinoma diagnosis, development and progression. The goal of this study is to evaluate part of some cytokines and biomarkers for both serum and saliva samples in breast cancer then estimate their potential value in the early diagnosis of breast cancer by doing more researches in saliva, and utilizing saliva instead of blood (serum and plasma) in sample collection from patients. Serum and salivary samples were taken from 72 patients with breast cancer and 45 healthy controls, in order to investigate the following
... Show MoreToday, 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
... Show MoreUrokinase plasminogen activator (uPA), urokinase plasminogen activator receptor (uPAR) and plasminogen activator inhibitor-1(PAI-1) are essential for metastasis, and overexpression of these molecules is strongly correlated with poor prognosis in a variety of malignant tumors. This study revealed direct correlation between immunohistochemical expression of uPA with pathological stage. No significant association of immunohistochemical expressions of uPA, uPAR and PAI-1 with immunohistochemical expressions for estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor -2 (HER-2/neu), and direct association between immunohistochemical expressions of (uPA and uPAR) as well as between immunohistochemical expr
... Show MoreBreast tumors patients generally have more oxidative stress than normal females. This was clear from a highly significant elevation (P<0.05) in malondialdehyde level in RBCs, serum and tissue of all patients groups with breast cancer as compared with control group. In this study we had found that free radicals in malignant breast tumors were higher than benign tumors, therefore the MDA might be used as a marker for prognosis of the disease.