Abstract
When dealing with biological organisms, one has to take into account some peculiarities
which significantly affect the representation of knowledge about them. These are complemented
by the limitations in the representation of propositional knowledge, i. e. the majority
of clinical knowledge, by artificial agents. Thus, the opportunities to automate the
management of clinical knowledge are widely restricted to closed contexts and to procedural
knowledge. Therefore, in dynamic and complex real-world settings such as health care
provision to HIV-infected patients human and artificial agents must collaborate in
order to optimize the time/quality antinomy of services provided. If applied to the
implementation level, the overall requirement ensues that the language used to model
clinical contexts should be both human- and machine-interpretable. The eXtensible
Markup Language (XML), which is used to develop an electronic study form, is evaluated
against this requirement, and its contribution to collaboration of human and artificial
agents in the management of clinical knowledge is analyzed.
Keywords
Knowledge Representation - Artificial Intelligence - eXtensible Markup Language (XML)
- Clinical Trial
