Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes

Vitor Cerqueira; Luis Torgo; Carlos Soares

doi:10.1007/978-3-030-33778-0_33

Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes

Vitor Cerqueira, Luis Torgo, Carlos Soares

Dentistry

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Original language	English
Title of host publication	Discovery Science 22nd International Conference, DS 2019, Proceedings
Editors	Petra Kralj Novak, Sašo Džeroski, Tomislav Šmuc
Publisher	Springer
Pages	445-459
Number of pages	15
ISBN (Print)	9783030337773
DOIs	https://doi.org/10.1007/978-3-030-33778-0_33
Publication status	Published - 2019
Event	22nd International Conference on Discovery Science, DS 2019 - Split, Croatia Duration: Oct 28 2019 → Oct 30 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11828 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Discovery Science, DS 2019
Country/Territory	Croatia
City	Split
Period	10/28/19 → 10/30/19

ASJC Scopus Subject Areas

Theoretical Computer Science
General Computer Science

Keywords

Early anomaly detection
Healthcare
Layered learning
Time series

Access to Document

10.1007/978-3-030-33778-0_33

Cite this

Cerqueira, V., Torgo, L., & Soares, C. (2019). Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes. In P. Kralj Novak, S. Džeroski, & T. Šmuc (Eds.), Discovery Science 22nd International Conference, DS 2019, Proceedings (pp. 445-459). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11828 LNAI). Springer. https://doi.org/10.1007/978-3-030-33778-0_33

Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes. / Cerqueira, Vitor; Torgo, Luis; Soares, Carlos.
Discovery Science 22nd International Conference, DS 2019, Proceedings. ed. / Petra Kralj Novak; Sašo Džeroski; Tomislav Šmuc. Springer, 2019. p. 445-459 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11828 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Cerqueira, V, Torgo, L & Soares, C 2019, Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes. in P Kralj Novak, S Džeroski & T Šmuc (eds), Discovery Science 22nd International Conference, DS 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11828 LNAI, Springer, pp. 445-459, 22nd International Conference on Discovery Science, DS 2019, Split, Croatia, 10/28/19. https://doi.org/10.1007/978-3-030-33778-0_33

Cerqueira V, Torgo L, Soares C. Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes. In Kralj Novak P, Džeroski S, Šmuc T, editors, Discovery Science 22nd International Conference, DS 2019, Proceedings. Springer. 2019. p. 445-459. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-33778-0_33

Cerqueira, Vitor ; Torgo, Luis ; Soares, Carlos. / Layered Learning for Early Anomaly Detection : Predicting Critical Health Episodes. Discovery Science 22nd International Conference, DS 2019, Proceedings. editor / Petra Kralj Novak ; Sašo Džeroski ; Tomislav Šmuc. Springer, 2019. pp. 445-459 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes

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ASJC Scopus Subject Areas

Keywords

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