Using artificial intelligence to predict childhood leukaemia outcomes

Lead researcher - Dr Amir Enshaei, Newcastle University
Cancer type - Childhood leukaemia
Development of machine learning system as a prediction tool in acute lymphoblastic leukaemia
Amount awarded: £217,437
Award start date: 01 Aug 2016
Award duration: 4 years (48 months)

It is now widely accepted that all leukaemia cells have at least one, but probably more, faulty genes, which are the cause of the disease. Knowing what gene changes are driving the leukaemia helps doctors with the diagnosis, and guides treatment decisions.

Due to advances in technology, researchers are finding more and more gene changes that are important in leukaemia, and the need for better outcome predictions tools are needed. One way is to use a advanced computational methods called ‘machine learning’, which uses artificial intelligence to automatically learn and improve from experience without being programmed by a human.

Using machine learning, Dr Amir Enshaei plans to gather and process clinical and genetic information from numerous ALL datasets. From this he plans to improve the most comprehensive dataset in the world, which will identify new risk groups in ALL. The final model will be available as a web-based prediction tool.