Breast Cancer Decisive Parameters for Iraqi Women via Data Mining Techniques

Abstract

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.

Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers

“…Early testing can increase protection from disease and make treatment more useful. In spite of trying to develop treatment but advance BC still hard goals of therapy range from symptom palliation to extending survival [1] [2]. Many reasons increase the risk of BC, like food, age, menarche, menopause, inheritance, and the number of children [3].…”

Effect of Selected Auditory Interventions on Reducing Chemotherapy Induced Anxiety and Pain of Children with Cancer and their Parents’ Satisfaction

“…(1&2) Over the precedent 10 years, the incidence of cancer has increased in the Middle East. (3) Each year, about 400,000 child and adolescent under 19 years of age developed cancer. The common types of cancer in children including leukemia, brain tumor, lymphomas, and solid tumors, such as neuroblastomas and Wilms' tumors.…”

Recitation of quran and music to reduce chemotherapy‐induced anxiety among adult patients with cancer: A clinical trial

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Cancer is still the main health problem worldwide and one of the highest leading cause of death around the world (National Cancer Institute, 2018;Siegel et al, 2019). Over the past 10 years, the prevalence of cancer has been increased in the Middle East, especially in Iraq (Behadili et al, 2019;Iraqi Cancer Board, 2018). Although many studies have been done regarding cancer, it remains a public health problem that needs to be considered by researchers (Siegel et al, 2019).

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