Development of Desktop Based Breast Cancer Symptoms Self-examination Support System

Abstract

Aims: The early identification of breast cancer is the most significant method for breast cancer prevention. Breast self-examination has received widespread support and promotion from cancer organisations and authorities worldwide. But for it to be effective, women need to be educated and reached out to, in addition to diligent and frequent self-examination. Breast screenings have been used for early detection of breast cancer, before any symptoms like palpable lumps or other symptoms become apparent. Study Design: Since medical practitioners relied mainly on the information supplied by patients regarding any ailment, there is a need to develop a standalone application that can be used for breast cancer self-examination for easy and early detection of cancer in women. Place and Duration of Study: Radiology Unit, LAUTECH Teaching Hospital, Oyo State, between September and December 2025; Federal Polytechnic Ede, Osun State. Methodology: A visibility study on breast cancer self-examination was conducted among selected respondents, and a standalone desktop application was then developed using Python and the PyQt library. The application guides users through a structured self-examination questionnaire and captures symptom-related responses. A rule-based logical decision framework was embedded in the system, where predefined clinical rules map reported signs and symptoms such as lumps, nipple discharge, skin changes, or persistent pain to decision outcomes. Based on the combination and severity of responses, the system classifies the user’s results as normal or requires further clinical assessments and recommends follow-up actions. Results: The results of the physical examination obtained from the respondents show that 18% of the respondents were abnormal and 82% were normal. These earlier symptoms, given by respondents, gave room for further advice to the 82% of respondents to go for mammogram tests. The application does not diagnose breast cancer and is not a substitute for clinical assessment. Rather, it functions as a screening support tool that flags the presence of symptoms or concerning changes that may require further medical evaluation. Conclusion: The developed desktop-based standalone application can be used by female individuals to perform a self-examination and by an expert to determine if there is a need to go for a mammography test or not.