The aim of this work is to investigate the effectiveness of novel human-machine interaction paradigms for eHealth applications. In particular, we propose to replace usual human-machine interaction mechanisms with an approach that leverages a chat-bot program, opportunely designed and trained in order to act and interact with patients as a human being. Moreover, we have validated the proposed interaction paradigm in a real clinical context, where the chat-bot has been employed within a medical decision support system having the goal of providing useful recommendations concerning several disease prevention pathways. More in details, the chat-bot has been realized to help patients in choosing the most proper disease prevention pathway by asking for different information (starting from a general level up to specific pathways questions) and to support the related prevention check-up and the final diagnosis. Preliminary experiments about the effectiveness of the proposed approach are reported.