title: Describing disease processes using a probabilistic logic of qualitative time.
abstract: BACKGROUND
  Clinical knowledge about progress of diseases is characterised by temporal information as well as uncertainty. However, precise timing information is often unavailable in medicine. In previous research this problem has been tackled using Allen's qualitative algebra of time, which, despite successful medical application, does not deal with the associated uncertainty.
  
  
  OBJECTIVE
  It is investigated whether and how Allen's temporal algebra can be extended to handle uncertainty to better fit available knowledge and data of disease processes.
  
  
  METHODS
  To bridge the gap between probability theory and qualitative time reasoning, methods from probabilistic logic are explored. The relation between the probabilistic logic representation and dynamic Bayesian networks is analysed. By studying a typical, and clinically relevant problem, the detection of exacerbations of chronic obstructive pulmonary disease (COPD), it is determined whether the developed probabilistic logic of qualitative time is medically useful.
  
  
  RESULTS
  The probabilistic logic extension of Allen's temporal algebra, called Qualitative Time CP-logic provides a tool to model disease processes at a natural level of abstraction and is sufficiently powerful to reason with imprecise, uncertain knowledge. The representation of the COPD disease process gives evidence that the framework can be applied functionally to a clinical problem.
  
  
  CONCLUSIONS
  The combination of qualitative time and probabilistic logic offers a useful framework for modelling knowledge and data to describe disease processes in clinical medicine.
authors.affiliation: Institute for Computing and Information Sciences, Radboud University Nijmegen, PO Box 9010, 6500GL Nijmegen, The Netherlands; Department of Primary and Community Care, Radboud University Nijmegen Medical Centre, PO Box 9101, 6500HB Nijmegen, The Netherlands. Electronic address: m.vanderheijden@cs.ru.nl.
authors.forename: Maarten
authors.initials: M
authors.lastname: van der Heijden
authors.forename: Peter J F
authors.initials: PJ
authors.lastname: Lucas
mesh_terms: D001499:Bayes Theorem; D018450:Disease Progression; D024882:Drug Resistance, Viral / Q000235:genetics; D015658:HIV Infections / Q000188:drug therapy; D006801:Humans; D011336:Probability; D029424:Pulmonary Disease, Chronic Obstructive / Q000473:pathology; D035501:Uncertainty
keywords: Chronic obstructive pulmonary disease; Dynamic Bayesian networks; Knowledge representation; Probabilistic logic; Temporal reasoning