My Topol fellowship problem / project:

Compared to other kidney replacement therapy modalities, kidney transplantation provides a higher quality of life and superior survival. However, the high demand for kidney transplants and the constrained supply are creating a vacuum in health systems around the world that is becoming increasingly difficult to close. One tactic is to give kidney grafts to recipients who will live the longest, which will decrease the frequency of graft failures and the number of patients who pass away while still having a functional graft. Prior to transplantation, risk prediction models can forecast graft failure, which is a clinical aid in the difficult decision-making process of choosing allografts with low failure risk and recipients who would live the longest. The question we will try to answer: Can we develop a predictive model using artificial intelligence to predict kidney graft survival pre and post-transplant? Would the artificial intelligence model give more accuracy and predictive ability compared to conventional survival analysis statistics (cox regression models)?

Study aims: Using time-to-event data from a sizable national dataset from the UK, our goal was to create and evaluate statistical and machine learning predictive models to predict graft failure following dead and living donor kidney transplant.

Data science experience: I am a Junior Data-scientist, having completed a post-graduate programme in Data science and Business analytics from Texas University, USA. I have been trained to work using Python during my course. I have also successfully completed 7 different supervised Machine learning projects during my course. These include exploratory data analysis, business statistics, linear and logistic regression, decision tree models, ensemble techniques, model tuning, and unsupervised learning.

Medical experience: I graduated from the Faculty of Medicine at Cairo University, Egypt and have been working as a doctor in the UK since 2015. I have joined the training programme in renal and GIM since 2017. I have also obtained Masters degree in Transplantation sciences from Liverpool university and currently a PhD student in Coventry University.

Research experience: I have many papers published in high impact factor journals including NDT (IF :6), CKJ (IF :4.5), Annals of Medicine (IF: 4.7), American journal of nephrology (IF: 3.5). Also, I have many oral presentations in national and international conferences. My role in these papers were literature search, data exploration and analysis and paper writing.