HF-Explain: a natural language generation system for explaining a medical expert system

Causal models have been used, with considerable success, to reason in the medical domain. While these systems typically have a robust reasoning mechanism and knowledge base about their specific area of expertise, their ability to satisfactorily explain their results in a meaningful, coherent and concise manner has been less impressive then their diagnostic capabilities. This paper describes a program, HF-Explain, that generates natural language explanations of one such system--the Heart Failure Program. HF-Explain, is loosely based on work done by McKeown in the Text system, using augmented transition networks (ATN) as a formalism to guide the explanation process. The result is a coherent, concise, accurate and rich explanation of Heart Failure Programs' diagnostic hypotheses.