TY - GEN
T1 - Towards a second generation of computer interpretable guidelines
AU - Terenziani, Paolo
AU - Bottrighi, Alessio
AU - Giordano, Laura
AU - Franceschinis, Giuliana
AU - Montani, Stefania
AU - Portinale, Luigi
AU - Dupre, Daniele Theseider
PY - 2013
Y1 - 2013
N2 - Computer Interpretable Guidelines (CIG) are an emerging area of research, to support medical decision making through evidence-based recommendations. However, new challenges in the data management field have to be faced, to integrate CIG management with a proper treatment of patient data, and of other forms of medical knowledge (e.g., causal and behavioral knowledge). In this position paper, we summarize a proposal for a research agenda that, in our opinion, can lead to a significant advancement in the field. The goal of the work is to provide suitable models and reasoning methodologies to cope with the aforementioned aspects, and to properly integrate them for medical decision support. Achieving such a goal requires advances in data management, and, in particular, in the treatment of indeterminate valid-time data in relational databases, of temporal abstraction on time series, of case retrieval on time series, of design-time and run-time model-based verification of guidelines, of case-based reasoning, of non-monotonic logics, of formal ontologies, of probabilistic graphical models (Bayesian Networks and Influence Diagrams).
AB - Computer Interpretable Guidelines (CIG) are an emerging area of research, to support medical decision making through evidence-based recommendations. However, new challenges in the data management field have to be faced, to integrate CIG management with a proper treatment of patient data, and of other forms of medical knowledge (e.g., causal and behavioral knowledge). In this position paper, we summarize a proposal for a research agenda that, in our opinion, can lead to a significant advancement in the field. The goal of the work is to provide suitable models and reasoning methodologies to cope with the aforementioned aspects, and to properly integrate them for medical decision support. Achieving such a goal requires advances in data management, and, in particular, in the treatment of indeterminate valid-time data in relational databases, of temporal abstraction on time series, of case retrieval on time series, of design-time and run-time model-based verification of guidelines, of case-based reasoning, of non-monotonic logics, of formal ontologies, of probabilistic graphical models (Bayesian Networks and Influence Diagrams).
KW - Analogical
KW - Computer interpretable guidelines
KW - Defeasible and probabilistic reasoning
KW - Integration of different forms of medical knowledge
KW - Logical
KW - Temporal data
UR - http://www.scopus.com/inward/record.url?scp=84887185034&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84887185034
SN - 9789898565679
T3 - DATA 2013 - Proceedings of the 2nd International Conference on Data Technologies and Applications
SP - 199
EP - 205
BT - DATA 2013 - Proceedings of the 2nd International Conference on Data Technologies and Applications
T2 - 2nd International Conference on Data Technologies and Applications, DATA 2013
Y2 - 29 July 2013 through 31 July 2013
ER -