Formal verification of CNL health recommendations

Clinical texts, such as therapy algorithms, are often described in natural language and may include hidden inconsistencies, gaps and potential deadlocks. In this paper, we propose an approach to identify such problems with formal verification. From each sentence in the therapy algorithm we automatically generate a parse tree and derive case frames. From the case frames we construct a state-based representation (in our case a timed automaton) and use a model checker (here UPPAAL) to verify the model. Throughout the paper we use an example of the algorithm for blood glucose lowering therapy in adults with type 2 diabetes to illustrate our approach.

Citation

Rahman , F & Bowles , J K F 2017 , Formal verification of CNL health recommendations . in N Polikarpova & S Schneider (eds) , Integrated Formal Methods : 13th International Conference, IFM 2017, Turin, Italy, September 20-22, 2017, Proceedings . Lecture Notes in Computer Science (Programming and Software Engineering) , vol. 10510 , Springer , Cham , pp. 357-371 , 13th International Conference on integrated Formal Methods (iFM 2017) , Torino , Italy , 18/09/17 . https://doi.org/10.1007/978-3-319-66845-1_24

conference

Publication

Integrated Formal Methods

DOI

https://doi.org/10.1007/978-3-319-66845-1_24

ISSN

0302-9743

Type

Conference item

Rights

© 2017, Springer International Publishing AG. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at link.springer.com / https://doi.org/10.1007/978-3-319-66845-1_24

Description

This research is partially supported by EPSRC grant EP/M014290/1.

Collections

University of St Andrews Research

URI

http://hdl.handle.net/10023/11693