A Machine Learning Approach to Diagnosing Breast Cancer
The study will gather data from large datasets containing symptoms of breast cancer, which coupled with the medical history of the patient and their family members, these cancers would be accurately diagnosed at the earliest stage possible.
The objectives of this research is to:
- Experiment different machine learning techniques and find out which is the best to predict the diagnosis of breast cancer at an earlier stage.The chosen model will be used for training purposes on the dataset and to build the model.
- Use the family history risk factor to have an insight as to whether a patient is more susceptible to be diagnosed with breast cancer or not.
- Verify the results of the model and its algorithms and extract notable conclusions from this study. These conclusions will then be presented to the Maltese medical community.
Michele La Ferla