Big data in IBD: big progress for clinical practice

#artificialintelligence 

Precision medicine holds great promise to improve the landscape of IBD course of care for an individual patient, providing the most beneficial therapy while minimising the risk. The ultimate goals of precision medicine include stratifying patients based on disease subtypes and severity, disease progression and treatment response using personal and clinical data coupled with molecular profiling data of patients.1 2 IBD, with its two main subtypes, Crohn's disease (CD) and UC, is a complex inflammatory disease with a wide range of contributing factors including host genetics, immune system, environmental exposures and the gut microbiome.3–5 The inherent complexity of the disease introduces a large number of confounding factors, which stand in the way of accurate diagnosis and precision medicine.6 The term'big data' is generally referred to as large volume of rapidly produced data from variable sources, known as the three'V's (volume, velocity and variety).7 Over the past decades, the production and availability of data that could inform healthcare has increased remarkably mainly due to technological advancements and falling costs of data generation.