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Modeling and detecting high-level events in healthcare applications exploiting ISEQL+.

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Title: Modeling and detecting high-level events in healthcare applications exploiting ISEQL+.
Authors: Persia, Fabio1 (AUTHOR) fabio.persia@univaq.it, Dignös, Anton2 (AUTHOR) anton.dignoes@unibz.it, Helmer, Sven3 (AUTHOR) helmer@ifi.uzh.ch, Gamper, Johann2 (AUTHOR) johann.gamper@unibz.it, D'Auria, Daniela4 (AUTHOR) daniela.dauria@unimib.it
Source: Soft Computing - A Fusion of Foundations, Methodologies & Applications. May2026, Vol. 30 Issue 5, p3667-3690. 24p.
Subjects: Query languages (Computer science), Medical informatics, Semantics, Video surveillance, Event processing (Computer science), Interval analysis, Relational databases
Abstract: Modeling and automatically detecting complex events in different domains, such as video surveillance and healthcare, is becoming an increasingly topical issue nowadays. In fact, deriving knowledge on higher level from low-level events by combining the latter to complex structures is the task of an Event Query Language (EQL), whose main issue is the lack of formal semantics. Consequently, in order to cope with this issue, in this paper we propose , an extension of ISEQL (an Interval-based Surveillance Event Query Language, that we previously defined), aimed at further improving its expressiveness. More specifically, we provide formal proofs demonstrating that the language fully covers the well-known Allen's interval relationships, additionally supports conditional overlap ratio and conditional cardinality constraints over the interval relationships, provides robustness with respect to small variations in the intervals, and can be formalized as relational algebra extension, which will in turn allow a very efficient implementation exploiting an existing algorithm. Eventually, we also show how typical events in the healthcare domain can be easily expressed via. [ABSTRACT FROM AUTHOR]
Copyright of Soft Computing - A Fusion of Foundations, Methodologies & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
An: 193654077
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  Data: Modeling and detecting high-level events in healthcare applications exploiting ISEQL+.
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  Data: <searchLink fieldCode="AR" term="%22Persia%2C+Fabio%22">Persia, Fabio</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> fabio.persia@univaq.it</i><br /><searchLink fieldCode="AR" term="%22Dignös%2C+Anton%22">Dignös, Anton</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> anton.dignoes@unibz.it</i><br /><searchLink fieldCode="AR" term="%22Helmer%2C+Sven%22">Helmer, Sven</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> helmer@ifi.uzh.ch</i><br /><searchLink fieldCode="AR" term="%22Gamper%2C+Johann%22">Gamper, Johann</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> johann.gamper@unibz.it</i><br /><searchLink fieldCode="AR" term="%22D'Auria%2C+Daniela%22">D'Auria, Daniela</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> daniela.dauria@unimib.it</i>
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  Data: <searchLink fieldCode="JN" term="%22Soft+Computing+-+A+Fusion+of+Foundations%2C+Methodologies+%26+Applications%22">Soft Computing - A Fusion of Foundations, Methodologies & Applications</searchLink>. May2026, Vol. 30 Issue 5, p3667-3690. 24p.
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  Data: <searchLink fieldCode="DE" term="%22Query+languages+%28Computer+science%29%22">Query languages (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+informatics%22">Medical informatics</searchLink><br /><searchLink fieldCode="DE" term="%22Semantics%22">Semantics</searchLink><br /><searchLink fieldCode="DE" term="%22Video+surveillance%22">Video surveillance</searchLink><br /><searchLink fieldCode="DE" term="%22Event+processing+%28Computer+science%29%22">Event processing (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Interval+analysis%22">Interval analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Relational+databases%22">Relational databases</searchLink>
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  Data: Modeling and automatically detecting complex events in different domains, such as video surveillance and healthcare, is becoming an increasingly topical issue nowadays. In fact, deriving knowledge on higher level from low-level events by combining the latter to complex structures is the task of an Event Query Language (EQL), whose main issue is the lack of formal semantics. Consequently, in order to cope with this issue, in this paper we propose , an extension of ISEQL (an Interval-based Surveillance Event Query Language, that we previously defined), aimed at further improving its expressiveness. More specifically, we provide formal proofs demonstrating that the language fully covers the well-known Allen's interval relationships, additionally supports conditional overlap ratio and conditional cardinality constraints over the interval relationships, provides robustness with respect to small variations in the intervals, and can be formalized as relational algebra extension, which will in turn allow a very efficient implementation exploiting an existing algorithm. Eventually, we also show how typical events in the healthcare domain can be easily expressed via. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Soft Computing - A Fusion of Foundations, Methodologies & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00500-025-10716-7
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      – Code: eng
        Text: English
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      – SubjectFull: Query languages (Computer science)
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      – SubjectFull: Medical informatics
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      – SubjectFull: Event processing (Computer science)
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      – SubjectFull: Interval analysis
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      – SubjectFull: Relational databases
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      – TitleFull: Modeling and detecting high-level events in healthcare applications exploiting ISEQL+.
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              M: 05
              Text: May2026
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              Y: 2026
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