Resources

Functional Status Information (FSI) describes physical and mental wellness at the whole-person level. It includes information on activity performance, social role participation, and environmental and personal factors affecting a person’s well-being and quality of life. Collecting, integrating, and analyzing this multi- modal information spanning different domains is crucial for addressing the needs of an aging global population and providing effective care for individuals with chronic conditions, multi-morbidity, and disabilities. Multi-Modal Knowledge Graphs represent a suitable way for integrating this information in a complete and structured way, allowing for reasoning and building tailored coaching solutions that support individuals in their daily lives for healthy living. FuS-KG aims to play a central role concerning the design and development of middle-layer applications of explainable behavior change systems allowing: (i) modeling conceptual information representing individuals’ FSI and the use of the information to adapt the generation of explanatory and motivational messages to the individual; (ii) supporting interoperability among different systems which could share, for example, databases of motivational messages or explainability algorithms; and, (iii) managing privacy and ethical issues relating to user data.

The COMMUNI.CARE (Communication and Patient Engagement at Diagnosis of Pancreatic Cancer) dataset is a set of 32 doctor-patient interactions at the time of pancreatic cancer diagnosis (PDAC).

Consecutive PDAC patients were enrolled at the time of diagnosis after obtaining informed consent in a single-center study for a total of 32 doctor-patient interactions. Data were audio-recorded, fully anonymized, and then transcribed. All data are in Italian.

The study has been conducted in San Raffaele Hospital, a large hospital in the North of Italy.