School of Medicine
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Colin Crooks

Clinical Associate Professor, Faculty of Medicine & Health Sciences

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Biography

Colin Crooks completed his undergraduate degree in Bachelor of Medicine, Bachelor of Surgery (BMBS) and B.Med.Sci (Hons) at University of Nottingham, before going on to receive his Diploma MRCP (UK) Royal College of Physicians and MSc in Epidemiology at London School of Hygiene and Tropical Medicine. He completed his PhD on Epidemiology of Upper Gastrointestinal bleeding at the University of Nottingham July 2013 funded by an MRC fellowship and Centenary Award, and is a Graduate Statistician (GradStat) after completing a MSc Statistics at the University of Sheffield.

Expertise Summary

Keywords:

Statistical Learning and Topic Modelling, Use and Analysis of Routine Databases, Mapping, Bayesian techniques, Gastroenterology, Multi-morbidity and Risk Assessment, Epidemiology

Research Summary

Colin Crooks has completed his PhD in the epidemiology of upper gastrointestinal bleeding studying its causes and outcomes using case control studies and survival analyses. This work was carried out… read more

Selected Publications

Current Research

Colin Crooks has completed his PhD in the epidemiology of upper gastrointestinal bleeding studying its causes and outcomes using case control studies and survival analyses. This work was carried out in linked the routine databases; (CPRD) Clinical Practice Research Datalink, (ONS) Office for National Statistics, and (HES) Hospital Episode Statistics. After returning to full time clinical training as a gastroenterologist and NIHR recognised Academic Clinical Assistant Professor. He has now completed training and has been appointed as a Clinical Associate Professor in Gastroenterology in the NDDC. Code from his current work on developing statistical learning methods for routine health data is available online at https://github.com/ColinCrooks/

Other areas of interest:

  • Defining exposures and outcomes in linked datasets
  • Measuring the burden of co-morbidity and frailty
  • Competing risk survival analysis
  • Hierarchical Bayesian analysis
  • Adverse effects in spontaneous report databases
  • Bayesian Topic Modelling
  • Efficient clinical trials using routine health care data

School of Medicine

University of Nottingham
Medical School
Nottingham, NG7 2UH

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