Abstract

Basically, medical diagnosis problems are the most effective component of treatment policies. Recently, significant advances have been formed in medical diagnosis fields using data mining techniques. Data mining or Knowledge Discovery is searching large databases to discover patterns and evaluate the probability of next occurrences. In this research, Bayesian Classifier is used as a Non-linear datamining tool to determine the seriousness of breast cancer. The recorded observations of the Fine Needle Aspiration (FNA) tests that are obtained at the University of Wisconsin are considered as experimental data set in this research. The Tabu search algorithm for structural learning of Bayesian classifier and Genie simulator for parametric learning of Bayesian classifier were used. Finally, the obtained results by the proposed model were compared with actual results. The comparison process indicates that seriousness of the disease in 86.18% of cases are guessed very close to the actual values by proposed model.Â

Highlights

  • EGFR and HER-2 are two members of ERbB/HER family of Type I Transmembrane growth factor receptors

  • What is the ethical strategy for this problem? Can doctors use truth-telling method for patients? Is patient – physician communication necessary to reduce illness and in the care of cancer patient? In this review, I will explain the ethical strategies for cancer treatment methods

  • Infection with Helicobacter pylori (Hp) plays an important role in the pathogenesis of peptic ulcer and is a risk factor for the development of adenocarcinoma and primary gastric lymphoma

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Summary

Introduction

EGFR and HER-2 are two members of ERbB/HER family of Type I Transmembrane growth factor receptors. According to over expression of three markers, EGFR, HER-2, and COX-2 in colorectal cancers, using drugs that act against these receptors and investigation of survival improvement of patients with these drugs in other studies are recommended [1-110]. A few studies identified HPV DNA in ovarian carcinoma tissues. Some studies did not detect HPV DNA in ovarian carcinoma tissues. We investigated the potential role of high risk HPVs in the ovarian epithelial carcinoma. Our findings could not support any association between high-risk oncogenic human papilloma virus (18 and 16) and malignant ovarian epithelial cancer. We investigated the Transcriptional effects of variety of metal ions on the bovine oxytocin and the thymidine kinase-ERE promoter by estrogen receptor αin MDA-MB 231 breast cancer cell line. The study revealed that some metal ions show estrogenic activity by classical or nonclassical mechanisms as well as some metal ions exhibit estrogenic activity by undetermined mechanisms in transfected MDA-MB 231 cell line [221-356]

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