  Complementary and alternative medicine are commonly used concomitantly with
conventional medications leading to adverse drug reactions and even fatality in
some cases. Furthermore, the vast possibility of herb-drug interactions
prevents health professionals from remembering or manually searching them in a
database. Decision support systems are a powerful tool that can be used to
assist clinicians in making diagnostic and therapeutic decisions in patient
care. Therefore, an original and hybrid decision support system was designed to
identify herb-drug interactions, applying artificial intelligence techniques to
identify new possible interactions. Different machine learning models will be
used to strengthen the typical rules engine used in these cases. Thus, using
the proposed system, the pharmacy community, people's first line of contact
within the Healthcare System, will be able to make better and more accurate
therapeutic decisions and mitigate possible adverse events.
