Applying deep learning on electronic health records in swedish to predict healthcare-associated infections

BioNLP 2016 - Proceedings of the 15th Workshop on Biomedical Natural Language Processing

Volumn , Issue , 2016, Pages 191-195

  Jacobson, Olof ^a   Dalianis, Hercules ^a  

^a STOCKHOLM UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

DEEP LEARNING; E-LEARNING; LEARNING ALGORITHMS; NATURAL LANGUAGE PROCESSING SYSTEMS;

AUTO ENCODERS; ELECTRONIC PATIENT RECORD; LEARNING METHODS; RESTRICTED BOLTZMANN MACHINE; SWEDISHS;

HEALTH CARE;

EID: 85120076596     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. Telmo Amaral, Luís M. Silva, Luís A. Alexandre, Chetak Kandaswamy, Jorge M. Santos, and Joaquim Marques de Sá. 2013. Using different cost functions to train stacked auto-encoders. In MICAI (Special Sessions), pages 114-120. IEEE.
2. Yoshua Bengio. 2009. Learning deep architectures for ai. Found. Trends Mach. Learn., 2(1):1-127, January.
3. Lars G Burman. 2006. Att förebygga vardrelaterade infektioner - ett kunskapsunderlag. Stockholm: Swedish National Board of Health and Welfare. ISBN, 595547553, (In Swedish).
4. Johan Carlberger, Hercules Dalianis, Martin Hassel, and Ola Knutsson. 2001. Improving precision in information retrieval for Swedish using stemming. In Proceedings of NODALIDA '01 - 13th Nordic Conference on Computational Linguistics.
5. Hercules Dalianis, Aron Henriksson, Maria Kvist, Sumithra Velupillai, and Rebecka Weegar. 2015. Health bank - a workbench for data science applications in healthcare. In Proceedings of the CAiSE-2015 Industry Track co-located with the 27th Conference on Advanced Information Systems Engineering - CAiSE 2015, pages 1-18, Stockholm, Sweden, June. CEUR.
6. Claudia Ehrentraut, Maria Kvist, Elda Sparrelid, and Hercules Dalianis. 2014. Detecting healthcareassociated infections in electronic health records: Evaluation of machine learning and preprocessing techniques. In Sixth International Symposium on Semantic Mining in Biomedicine (SMBM 2014), Aveiro, Portugal, October 6-7, 2014, pages 3-10. University of Aveiro.
7. Claudia Ehrentraut, Markus Ekholm, Hideyuki Tanushi, Jörg Tiedemann, and Hercules Dalianis. 2016. Detecting hospital acquired infections: A document classification approach using support vector machines and gradient tree boosting. Health Informatics Journal, To be published.
8. Rachel Freeman, Luke S. P. Moore, Laura García Álvarez, Andre Charlett, and Alison Holmes. 2013. Advances in electronic surveillance for healthcareassociated infections in the 21st Century: A systematic review. Journal of Hospital Infection.
9. Hilary Humphreys and Edmund T. M. Smyth. 2006. Prevalence surveys of healthcare-associated infections: what do they tell us, if anything? Clinical Microbiology and Infection, 12(1):2-4.
10. Stephen Marsland. 2009. Machine Learning: An Algorithmic Perspective. Chapman & Hall/CRC, 1st edition.
11. Denys Proux, Pierre Marchal, Frédérique Segond, Ivan Kergourlay, Stéfan Darmoni, Suzanne Pereira, Quentin Gicquel, and Marie-Hélène Metzger. 2009.
12. Natural Language Processing to detect Risk Patterns related to Hospital Acquired Infections. In Proceedings of the Workshop Biomedical Information Extraction, pages 35-41. Association for Computational Linguistics.
13. Denys Proux, Caroline Hagège, Quentin Gicquel, Suzanne Pereira, Stefan Darmoni, Frédérique Segond, and Marie-Hélène Metzger. 2011. Architecture and Systems for Monitoring Hospital Acquired Infections inside a Hospital Information Workflow. In Proceedings of the Workshop on Biomedical Natural Language Processing. USA: Portland, Oregon, pages 43-48. Citeseer.
14. Radim Řehuřek and Petr Sojka. 2010. Software Framework for Topic Modelling with Large Corpora. In Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks, pages 45-50, Valletta, Malta, May. ELRA. http://is. muni.cz/publication/884893/en.
15. Hideyuki Tanushi, Maria Kvist, and Elda Sparrelid. 2015. Detection of Healthcare-Associated Urinary Tract Infection in Swedish Electronic Health Records. Innovation in Medicine and Healthcare 2014, 207:330.
16. Tijmen Tieleman. 2008. Training restricted Boltzmann machines using approximations to the likelihood gradient. In Proceedings of the 25th international conference on Machine learning, pages 1064-1071.
17. Alper Kursat Uysal and Serkan Gunal. 2014. The impact of preprocessing on text classification. Information Processing and Management, 50(1):104-112.
18. Peratham Wiriyathammabhum, Boonserm Kijsirikul, Hiroya Takamura, and Manabu Okumura. 2012. Applying deep belief networks to word sense disambiguation. CoRR, abs/1207.0396.