@inproceedings{58013ef956a74f478b71b014a615aa5f,
title = "A general approach to represent and query now-relative medical data in relational databases",
abstract = "Now-related temporal data play an important role in the medical context. Current relational temporal database (TDB) approaches are limited since (i) they (implicitly) assume that the span of time occurring between the time when facts change in the world and the time when the changes are recorded in the database is exactly known, and (ii) do not explicitly provide an extended relational algebra to query now-related data. We propose an approach that, widely adopting AI symbolic manipulation techniques, overcomes the above limitations.",
keywords = "Now-related data, Temporal algebra, Temporal relational databases",
author = "Luca Anselma and Luca Piovesan and Abdul Sattar and Bela Stantic and Paolo Terenziani",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 15th Conference on Artificial Intelligence in Medicine, AIME 2015 ; Conference date: 17-06-2015 Through 20-06-2015",
year = "2015",
doi = "10.1007/978-3-319-19551-3_41",
language = "English",
isbn = "9783319195506",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "327--331",
editor = "Riccardo Bellazzi and Lucia Sacchi and Holmes, {John H.} and Niels Peek",
booktitle = "Artificial Intelligence in Medicine - 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Proceedings",
address = "Germany",
}