Machine learning brings an early diagnostic for pancreatic cancer a step closer to reality

Individuals at higher risk of developing pancreatic cancer could be identified earlier using machine learning (ML) techniques which would result in a greater number of patients surviving the disease, suggests a new study published in PLOS ONE. The study was led by the London School of Hygiene & Tropical Medicine (LSHTM) and funded by the UK charity Pancreatic Cancer Research Fund (PCRF). It used UK electronic health records for more than 1,000 patients aged 15-99 years who were diagnosed with pancreatic cancer between January 2005 and June 2009. The researchers examined numerous symptoms and health statuses recorded by a GP among patients up to two years before the cancer diagnosis. They then developed an algorithm which'learnt' how to distinguish patients who went on to develop pancreatic cancer from those who didn't.