The term "medical informatics" refers to the discipline that studies how to represent, analyze and communicate biomedical data and knowledge, both within a single health care organization and between different organizations, often including the patient's home. Moreover, it deals with the information science and the technology to support these tasks.

The aim of medical informatics in our laboratory is the design and development of systems aimed at supporting patients and medical staffs in the various stages of the clinical path. Examples of physician-addressed systems are: computerized clinical practice guidelines, generating recommendations according to the best scientific evidence; careflow management systems, allowing the different healthcare operators sharing data and knowledge efficiently; process mining systems, allowing to capture healthcare professionals' behaviour starting from system logs; decision trees, supporting the physician in taking decisions according to utility theory. The latter are also used for the so-called "shared decisions" where patients and physicians together reason about unclear situations before taking a final decision about a treatment.  Examples of patient-addressed systems are: telemedicine and tele-homecare systems, often based on body area networks of sensors, able to provide a safer patient's monitoring and a light decision support for those (non-critical) situations in which the patient himself is allowed to change his therapy (e.g.  adjusting insulin doses according to daily glycemia measurements); software tools for home cognitive rehabilitation; questionnaire administration methods for measuring the patients' quality of life, as a means for measuring a treatment effect.

Eventually, since health care institutions are more and more paying attention to cost containment, our lab developed also expertise on economic evaluations of healthcare programmes (cost-effectiveness and cost-utility studies), offering decision support for policy makers.

Although aimed at the development of applications, research play a vital role in our lab. The main research areas are knowledge representation, understanding and elicitation of cognitive processes,  ontologies for representing medical domains entities and their relationships, and decision theory.