Mustapha Diyaol Haqq is a Ghanaian high school student who created a system that uses predictive analytics model to predict breast cancer. He is also a Content Developer, Code Instructor and Volunteer at Ghana Code Club where he teaches and inspire kids to code.
The Machine Learning/Artificial Intelligence system is such that, given breast cancer results from breast fine needle aspiration (FNA) test (is a quick and simple procedure to perform, which removes some fluid or cells from a breast lesion or cyst (a lump, sore or swelling) with a fine needle similar to a blood sample needle), the model can classify a breast cancer tumor using two training classification:
- 1= Malignant (Cancerous) – Present
- 0= Benign (Not Cancerous) –Absent
“The goal is to classify whether the breast cancer is benign or malignant and predict the recurrence and non-recurrence of malignant cases after a certain period. To achieve this we used machine learning classification methods to fit a function that can predict the discrete class of new input.”
The model was trained and tested using the Breast Cancer datasets available on the machine learning repository maintained by the University of California, Irvine. The dataset contains 569 samples of malignant and benign tumor cells.
“We’ve shown it is possible to predict and diagnose Breast Cancer with Machine Learning/ Artificial Intelligence. We are confident with larger data of Ghanaians, models could be developed with higher accuracy scores that could be used in the real world by doctors to diagnose breast cancer efficiently, with ease and a higher accuracy” – Diyaol Haqq
Mustapha Diyaol Haqq has also published his first research paper on using Predictive Analysis To Diagnose Breast Cancer. You can request for the research paper by emailing him: firstname.lastname@example.org.