Risk Prediction Model for Endometrial Cancer using multiple Machine Learning Algorithms and Meta-Analysis
The aim of this project is to create a piece of software which can assist physicians to make better decisions and help patients make an informed choice about their treatment in endometrial cancer.
Find an accurate percentage of risk for each individual risk factor. (That was done by the meta-analysis I concluded)
Find correlations between risk factors.
Create a model which predicts patients with endometrial cancer.
Provide personalised prevention techniques to reduce risk according to the patient’s exposure to risk factors.
On this project I am collaborating with my supervisor Annette Payne