IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 2, March 2011 ISSN (Online): 1694-0814 www.IJCSI.org 501 Decision Support System for Histopathological Diagnosis of Breast Diseases in Women Aderonke A. Kayode 1 , Babajide S. Afolabi 2 , Bernard I. Akhigbe 3 , Ifiok J. Udo 4 and A. Ominiyi 5 Information Storage and Retrieval Group Department of Computer Science & Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria. Abstract This paper presents a representation of histological features for histopathological diagnosis of breast diseases in women. Hence, a Decision Support System (DSS) for histopathological interpretation and diagnosis of breast diseases was implemented and evaluated. The Expert knowledge used was elicited through interview and literature search. The needed diagnostic knowledge was represented using diseases’ profile in the form of frame. UML, JAVA and MYSQL were used for the design and implementation of the system. 150 samples of retrospective cases were used for the system’s implementation, while a Consultant Pathologist’s interpretation was used to evaluate the system. Results for Sensitivity, Specificity, Positive Prediction Value and the Negative Prediction Value are 97.7%, 95.0%, 99.2% and 86.3% respectively. Thus, the result showed that the system is capable of assisting an inexperience pathologist in making accurate, consistent and timely diagnoses, also in the study of diagnostic protocol, education, self-assessment, and quality control. Keywords: Histological features, Histopathological diagnosis, Expert knowledge, Diagnostic knowledge, Pathologist, Decision Support System 1. INTRODUCTION Histopathological interpretation of multiple types of tissue and cytological specimens do provide crucial information. The accuracy of this information is critical to the provision of good health care. Tissue evaluations are generally viewed as “gold standard” medical facts that provide the highest quality, most reliable, diagnostic evidence available. There is likely no investigative modality that can match the economic yield of information available to a skilled pathologist, when interpreting a tissue section stained with basic hematoxylin and eosin [1], [2], [3]. However, the diagnosis of breast diseases using histopathological means requires both visual and logical skills to accurately interpret microscopic images. The cognitive heuristics involved in the recognition of pathologic visual patterns are clearly related to training and experience. But the decision-making processes involved in this realm are poorly defined. As in many situations, the quality of decisions is important; aiding the deficiencies of human judgment and decision making has been a major focus of science throughout history [4]. The concept of a Decision Support System (DSS) is extremely broad and its definitions vary depending on the author’s point of view [4]. But first, decisions are often the choices made between alternatives and are based on estimates of the values of these alternatives. Hence, supporting a decision means helping people (who work alone or in a group), to gather intelligence, generate alternatives and make choices. The DSS is usually referred to as computer applications that perform this type of supporting role. They can take any different forms and can be used in many different ways [5]. [6] defined it as “a computer-based system that aids the process of decision making”. More precisely, [7] defined it as an interactive, flexible, and adaptable computer-based information system. The system specially developed for providing solution to non-structured management problem for improved decision making, utilizes data, provides an easy- to-use interface, as well as allow the decision maker’s own insights to be uninfluenced. For [8], it is an interactive computer based system that help decision makers utilize data and models to solve unstructured problems. As a