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
