Kari Sentz

The objective of evidence-based medicine is to come to well reasoned and justified clinical decisions regarding an individual patient’s case based on the integration of case-specific knowledge, medical expertise, and the best available clinical evidence. One significant challenge implicated in this pursuit stems from the volume of relevant information that can easily exceed what can reasonably be assessed. Thus intelligent systems that can mine and synthesize vast amounts of information would be invaluable. The reconciliation of such systems with the complexity and subtlety of decision support in medicine requires specialized capabilities. One untapped capability is furnished through the gap in information between what is known and what needs to be known to justify a decision. In this paper, we explore the value of an information gap analysis for robust decision-making in the context of evidence-based medicine with an eye to the potential role in automated evidence-based reasoning systems.