Smart Breast Cancer Predictor
Date
2021-04-27Author
Niyonsaba, Alex
Okoth, Brian
Mutungi, Dennis Sharp
Kalema, Arnold
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Show full item recordAbstract
Breast cancer in Uganda is the third commonest cancer in women, coming only next to cancer of
the cervix and Kaposi's sarcoma. In this Project (SBCP), the Smart Breast Cancer Predictor
Project members investigated how breast cancer is diagnosed in Uganda. The SBCP team
members found out that the mammogram image is commonly used in diagnosis of breast cancer,
the doctor spends more time (average of 18 minutes) to diagnose a single patient, and the number
of breast cancer specialists is relatively small. Basing on the results of the study, we proposed to
address the issues that we found out, by developing Smart Breast Cancer Predictor System to
effectively predict breast cancer basing on mammogram images.
SBCP takes a mammogram image as its input, analyses it to find out whether there is presence of
Breast Cancer. It provides graphical analysis of the rate of spread of breast cancer, keep track of
patients’ breast cancer prediction results, and notifies patients whose results are predicted to be
positive about the next checkup.
The SBCP will mainly operate in health centers that handle issues related to breast cancer.