Analyses of health information

An important theme of CHIMR is to examine innovative ways of using non-statistical methods to analyse health data and information. One of the areas of interest is to explore the use of graph theory to identify patterns of deprivation and disease in public health data sets. Another area is examing AI methods to analyse data relating to health and well-being in older people.

The following papers have been published:

  • Read S, Bath PA, Willett P and Maheswaran R (2013) New developments in the spatial scan statistic. Journal of Information Science. 39(1): 36-47.
  • Pecchia L, Bath PA, Pendleton N and Bracale M (2011) Use of the Analytic Hierarchy Process (AHP) for examining healthcare professionals’ assessments of the relative importance of risk factors for falls in community-dwelling older people. Methods of Information in Medicine. 50 (5): 435-444.
  • Read S, Bath PA, Willett P and Maheswaran R (2011) Measuring the Spatial Accuracy of the Spatial Scan Statistic. Spatial and Spatio-temporal Epidemiology. 2 (2): 69-78.
  • Pecchia L, Bath PA, Pendleton N., Bracale M (2010) Web-based system for assessing risk factors for falls in community-dwelling elderly people using the analytic hierarchy process. International Journal of the Analytic Hierarchy Process. 2(2): 135-157.
  • Bath PA, Deeg D and Poppelaars J (2010) The harmonisation of longitudinal data: a case study using data from cohort studies in The Netherlands and the United Kingdom. Ageing and Society. 30(8):1419-1437.
  • Pecchia L, Schiraldi F, Verde S, Mirante E, Bath PA and Bracale M (2010) Evaluation of Short-Term Effectiveness of the Disease Management Program “Di.Pro.Di.” in Continuity of Care of Patients Suffering from Congestive Heart Failure. Research Letter. Journal of the American Geriatrics Society. 58 (8): 1603-1604.
  • Ahmad R, Samy GN, Bath PA and Ismail Z (2010) Threats Identification in Healthcare Information Systems using Genetic Algorithm and Cox Regression. Journal of Information Assurance and Security. 5:154-161.
  • Maheswaran R, Read S, Craigs C, Bath PA and Willett P (2009) A graph-theory method for pattern identification in geographical epidemiology – a preliminary application to deprivation and mortality. International Journal of Health Geographics. 8. Art. No.28. ISSN 1476-072X.
  • Bath PA, Craigs C, Maheswaran R, Raymond J and Willett P (2005) Use of graph theory to identify patterns of deprivation, high morbidity and mortality in public health data sets. Journal of the American Medical Informatics Association. 12: 630-641.
  • Bath PA, Craigs C, Maheswaran R, Raymond J and Willett P (2005) Use of graph theory to identify patterns of deprivation, high morbidity and mortality in public health data sets. Journal of the American Medical Informatics Association. 12: 630-641.
  • Ahmad R and Bath PA (2004) The use of Cox regression and genetic algorithm (CoRGA) for identifying risk factors for mortality in older people. Health Informatics Journal. 10 (3): 221-236.
  • Ahmad R and Bath PA (2004) The use of Cox regression and genetic algorithm (CoRGA) for identifying risk factors for mortality in older people. Health Informatics Journal. 10 (3): 221-236.
  • Bath PA (2004) Data mining in health and medical information. Annual Review of Information Science and Technology. Volume 38:331-369.
  • Bath P, Craigs C, Maheswaran R, Raymond J and Willett P (2002) Validation of graph-theoretical methods for pattern identification in public health datasets. Health Informatics Journal. 8:167-173.