Big data analytics for holistic understanding of impact of exercise on health and disease

The totality of data related to patient health and wellbeing make up so-called “Big Data” in the healthcare industry. The advent of Big Data (Biobank and electronic health records) has opened new and exciting avenues to progress our understanding of interactions between exercise, ageing and the progression of chronic disease. For the purpose of big data analytics this raw data needs to be pooled, processed or transformed, at which point several options are available. The relevant four typical applications of big data analytics in healthcare would be considered; namely queries, reports, OLAP, and data mining. Visualization is an overarching theme across these four applications. Drawing from such fields as information technology, clinical physiology and exercise epidemiology, a wide variety of techniques and technologies will be developed and adapted to aggregate, manipulate, analyse and visualise big data that contribute to the generation of new knowledge of interactions between exercise, ageing and chronic disease.

Supervision: Prof Fergal Grace (Principal), Assoc Prof Madhu Chetty (Associate), Prof Britt Klein (Associate)

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