The enormous volume of data produced in the context of healthcare processes has determined the need to develop advanced analytical techniques useful for management purposes. In particular, clinical research and some medical practices are experiencing a radical change related to the introduction of learning algorithms that can facilitate the analysis of a considerable amount of data relating to healthcare. Artificial intelligence allows the integration of guidelines in decision support systems and clinical workflow promising prospects for standardization and improvement of the quality of healthcare. Through artificial intelligence techniques, it is possible to proceed with the construction of algorithms capable of learning from past events and predicting unknown events. The implementation of predictive modelling tools for clinical decision-making support represents one of the most advanced technological solutions to be developed in the software field. The application of similar systems in the clinical field and - more precisely - in the medico-legal activities of necropsy and litigation management presupposes a rigorous methodological framework that allows to overcome the skepticism shown by healthcare professionals and encourage the replacement of systems currently used. The objective of the present project is to develop an infrastructure for the development of a medico-legal decision support system field in the form of a set of objective and standardized tools. The system must be able to provide diagnostic considerations auxiliary to the autopsy activity, as well as to carry out risk assessments in healthcare liability litigation, and to find a link between exposure and possible diseases in the health surveillance of workers. The purpose corresponds to the introduction and application of scientific evidence to the typical functions of the medico-legal and occupational medicine activities carried out in the context of the National Health System.
