Abstract

In Africa, the prevalence of unexpected deaths due to various illnesses highlights the urgent need for improved medical care systems. Breast cancer is a common cancerous infections found among women and also the primary cause of death of females living with cancer around the World. This paper proposes the development of a fuzzy model for cancer of the breast prediction, aiming to mitigate the shortcomings of traditional diagnostic approaches. By leveraging fuzzy logic, the model seeks to improve the precision and reliability in predicting the cancer of the breast, thereby facilitating earlier detection and intervention. In evaluation, the model demonstrates promising performance metrics with an Accuracy of 84%, Precision of 81.8%, Recall of 81.8%, and F1-score of 81.6%. The system was developed using the application development kit of Visual Studio C# for the code construct of forms interaction with EMGU profiler for image processing, training and matching, as well as MS SQL server for its backend to store information. The design of a Fuzzy Model for Breast Cancer Prediction is expected to enhance diagnostic accuracy, providing personalized treatment recommendations. By integrating fuzzy logic, it aims to reduce false results, ensuring timely intervention and minimizing unnecessary medical procedures for patients. The software methodology employed in the system is Object-Oriented Methodology. This research addresses a critical gap in healthcare delivery in Africa, offering a potentially transformative approach to combating the devastating impact of breast cancer through improved predictive analytics.