Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis.
Journal:
Computer methods and programs in biomedicine
Published Date:
May 4, 2017
Abstract
BACKGROUND AND OBJECTIVES: This paper examines the accuracy and efficiency (time complexity) of high performance genetic data feature selection and classification algorithms for colon cancer diagnosis. The need for this research derives from the urgent and increasing need for accurate and efficient algorithms. Colon cancer is a leading cause of death worldwide, hence it is vitally important for the cancer tissues to be expertly identified and classified in a rapid and timely manner, to assure both a fast detection of the disease and to expedite the drug discovery process.