Computerized database management system for breast cancer patients
نویسندگان
چکیده
Data analysis based on breast cancer risk factors such as age, race, breastfeeding, hormone replacement therapy, family history, and obesity was conducted on breast cancer patients using a new enhanced computerized database management system. My Structural Query Language (MySQL) is selected as the application for database management system to store the patient data collected from hospitals in Malaysia. An automatic calculation tool is embedded in this system to assist the data analysis. The results are plotted automatically and a user-friendly graphical user interface is developed that can control the MySQL database. Case studies show breast cancer incidence rate is highest among Malay women, followed by Chinese and Indian. The peak age for breast cancer incidence is from 50 to 59 years old. Results suggest that the chance of developing breast cancer is increased in older women, and reduced with breastfeeding practice. The weight status might affect the breast cancer risk differently. Additional studies are needed to confirm these findings.
منابع مشابه
A Hierarchical Classification Method for Breast Tumor Detection
Introduction Breast cancer is the second cause of mortality among women. Early detection of it can enhance the chance of survival. Screening systems such as mammography cannot perfectly differentiate between patients and healthy individuals. Computer-aided diagnosis can help physicians make a more accurate diagnosis. Materials and Methods Regarding the importance of separating normal and abnorm...
متن کاملA New Knowledge-Based System for Diagnosis of Breast Cancer by a combination of the Affinity Propagation and Firefly Algorithms
Breast cancer has become a widespread disease around the world in young women. Expert systems, developed by data mining techniques, are valuable tools in diagnosis of breast cancer and can help physicians for decision making process. This paper presents a new hybrid data mining approach to classify two groups of breast cancer patients (malignant and benign). The proposed approach, AP-AMBFA, con...
متن کاملPrediction Axillary Lymph Node Involvement Status on Breast Cancer Data
Introduction: one of the foremost usual methods for evaluating breast cancer is the removal of axillary lymph nodes (ALN) which include complications such as edema, limited hand movements, and lymph accumulation. Although studies have shown that the sentinel gland condition represents the axillary nodules context in the mammary gland, the efficacy, and safety of the guard node biopsy need to be...
متن کاملBreast Cancer Risk Assessment Using adaptive neuro-fuzzy inference system (ANFIS) and Subtractive Clustering Algorithm
Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used. First,...
متن کاملBreast Cancer Risk Assessment Using adaptive neuro-fuzzy inference system (ANFIS) and Subtractive Clustering Algorithm
Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used. First,...
متن کامل