A collaborative decision-support system for secure analysis of cranial disorders

Nowadays cranial disorders are one of the most common type of infants' diseases. However, despite such disorders are widespread, in the state of the art does not exist a system which allows the doctors to share their knowledge in order to support their clinical decisions. This is mainly caused by the different national laws governing the access to information concerning minors. However, it is important to emphasize that such limited access during the decision-making process, is one of the main causes of medical errors, and clearly can lead to serious consequences for the patient's health.In order to overcome the above defined issues, we first propose an engine for the automatic analysis of the patients' cranial data, which allows to detect end quantify eventual disorders. In addition, we propose a collaborative decision support system to enable the secure storing, sharing and analysis of clinically relevant information, which allows to not violate the patients' privacy. In particular, the collaborative system we propose, enables the doctors to rely on a previously acquired base of knowledge, as well as on the opinions of other doctors, during all the phases necessary to carry out the analysis and the clinical evaluation of the patient under examination.The proposed collaborative system can represent a valuable and effective aid for the doctors in charge of such disorders, even allowing to overcome the limitations imposed by national law.