Modeling fatigue

Proc AMIA Symp. 2002:747-51.

Abstract

The American Board of Family Practice is developing a patient simulation program to evaluate diagnostic and management skills. The simulator must give temporally and physiologically reasonable answers to symptom questions such as "Have you been tired?" A three-step process generates symptom histories. In the first step, the simulator determines points in time where it should calculate instantaneous symptom status. In the second step, a Bayesian network implementing a roughly physiologic model of the symptom generates a value on a severity scale at each sampling time. Positive, zero, and negative values represent increased, normal, and decreased status, as applicable. The simulator plots these values over time. In the third step, another Bayesian network inspects this plot and reports how the symptom changed over time. This mechanism handles major trends, multiple and concurrent symptom causes, and gradually effective treatments. Other temporal insights, such as observations about short-term symptom relief, require complimentary mechanisms.

MeSH terms

  • Artificial Intelligence*
  • Bayes Theorem
  • Clinical Competence*
  • Computer Simulation*
  • Educational Measurement / methods
  • Family Practice / education
  • Family Practice / standards
  • Fatigue*
  • Humans
  • Hypothyroidism / diagnosis
  • Hypothyroidism / therapy
  • Patient Simulation*