Data Clustering

Through this service, specialized clinical data sets for each single pathology (‘Data Mart’) can be created collecting and integrating data of different sources to provide a consistent and patient-centered view. The data set can include both retrospective and prospective data collected in the context of a clinical study or symptom detection, and quality of life indicators can be integrated using wearable devices as in the case of Patient Reported Outcome Measures (PROMs) and Patient Reported Experience Measures (PREMs). The Data Clustering service includes a phase of “data discovery” from unstructured data (for example through text mining for clinical reports) aimed at transforming “data” into “information”, and a series of quality assurance procedures to guarantee the quality and consistency of the data integrated into the DataMart. The Data Clustering service is functional: descriptive analysis, statistical analysis, and predictive models of machine learning/artificial intelligence.