|Title||Supporting tele-health and AI-based clinical decision making with sensor data fusion and semantic interpretation: The USEFIL case study|
|Publication Type||Conference Paper|
|Year of Publication||2012|
|Authors||Artikis, Alexander, Bamidis Panagiotis, Billis Antonis, Bratsas Charalampos, Frantzidis Christos A., Karkaletsis Vangelis, Klados Manousos, Konstantinidis Evdokimos, Konstantopoulos Stasinos, Kosmopoulos Dimitris, Papadopoulos Homer, Perantonis Stavros, Petridis Sergios, and Spyropoulos Constantine|
|Conference Name||International workshop on artificial intelligence and NetMedicine|
|Conference Location||Montpellier, France|
We propose a three-layered architecture for clinical evidencebased Decision Support Systems. Our architecture allows for off-the-shelf low-cost sensors to be deployed in tele-health environments; counterbalancing low confidence in the sensor data by fusing data from multiple sensors. The relevant data fusion and interpretation layer also forms the interface between sensor data and explicit rules encoding medical knowledge. This achieves a complete separation of the non-medical and medical knowledge, an important step for system adoption.