Drug resistance enables cancer cells to break away from cytotoxic effect of anticancer drugs. Identification of resistant phenotype is very important because it can lead to effective treatment plan. There is an interest in developing classifying models of resistance phenotype based on the multivariate data. We have investigated a vibrational spectroscopic approach in order to characterize a...

Introduction Breast cancer is one of the most common types of cancer among women.  Early detection of breast cancer is the key to reducing the associated mortality rate. The presence of microcalcifications clusters (MCCs) is one of the earliest signs of breast cancer. Due to poor imaging contrast of mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially t...

Cancer is a fatal disease that constantly changing and affects vast number of individuals worldwide. At the research level, much work has gone into creation improvement techniques built on data mining approaches allow for early identification prevention breast cancer. Because its excellent diagnostic abilities effective classification, technologies have reputation in medical profession continua...

A number of different approaches based on high-throughput data have been developed for cancer classification. However, these methods often ignore the underlying correlation between the expression levels of different biomarkers which are related to cancer. From a biological viewpoint, the modeling of these abnormal associations between biomarkers will play an important role in cancer classificat...

Cancer classification is the critical basis for patient-tailored therapy, while pathway analysis is a promising method to discover the underlying molecular mechanisms related to cancer development by using microarray data. However, linking the molecular classification and pathway analysis with gene network approach has not been discussed yet. In this study, we developed a novel framework based ...

The Piver classification of radical hysterectomy for the treatment of cervical cancer is outdated and misused. The Surgery Committee of the Gynecological Cancer Group of the European Organization for Research and Treatment of Cancer (EORTC) produced, approved, and adopted a revised classification. It is hoped that at least within the EORTC participating centers, a standardization of procedures ...

In this study, we propose a new feature (or gene) selection algorithm using Bayes classification approach. The algorithm can find gene subset crucial for cancer classification problem. Problem statement: Gene identification plays important role in human cancer classification problem. Several feature selection algorithms have been proposed for analyzing and understanding influential genes using ...

The k nearest neighbor classification method is one of the humblest method in conceptually and it is a top method in image mining. In this work, the enhanced k nearest neighbor (EKNN) technique has been implemented to identify the cancer and automatic classification of benign and malignant tissues in the huge amount of lung cancer image datasets. In this proposed system, we have used three stag...

background: rhabdomyosarcoma is a rare malignant soft tissue sarcoma and the most common sarcoma of childhood. the purpose of this study was to investigate the distribution of age and sex of patients, pathological subtypes and to determine the role of staging and classification of rms on treatment outcome. materials and methods: this retrospective study included patients who diagnosed with rms ...