A molecular allergy diagnosis based on microarray technology may sometimes be a complex task due to the large number of results available, the relationships between the components and the rules that govern virtually every single component. For this reason, a computer-assisted tool based on data from the literature, international guidelines and experts’ opinion may play a significant role, particularly in countries where these molecular tools are only recently available.

"Expert systems are a part of the artificial intelligence (AI) world; however, because they belong to the knowledge-based systems, ESs are not considered auto-learning tools. They are intended to act as human experts consulted to obtain advice, suggestions and recommendations on problems that fall within the experts’ knowledge. Thus, during the development of an ES, the external consultants indicate both the objects that are involved and the rules that govern these objects."

The strengths of this approach are numerous. In general, ESs are characterized by:

• the consistency and traceability of the results compared to an individual’s interpretation;
• the productivity gains (less expensive than an expert);
• the performance gains (quicker than humans);
• the availability of the solution (can be available anytime, anywhere).

As Allergenius is an ES written by MDs for MDs, special attention was given to the construction of the report. For example, the above-mentioned level of detail can be defined by the user. Thus, experts will not be obliged to read that Der p 1 is a cysteine protease or that Dermatophagoides pt. belongs to the Pyroglyphidae family, and novices will not be confused by too much data. If needed, further information is available using a dedicated hypertext link.