Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Learning from Administrative Health Registries
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Show others and affiliations
2017 (English)In: SoGood 2017: Data Science for Social Good: Proceedings / [ed] Ricard Gavaldà, Irena Koprinska, Stefan Kramer, CEUR-WS.org , 2017Conference paper, Published paper (Refereed)
Abstract [en]

Over the last decades the healthcare domain has seen a tremendous increase and interest in methods for making inference about patient care using large quantities of medical data. Such data is often stored in electronic health records and administrative health registries. As these data sources have grown increasingly complex, with millions of patients represented by thousands of attributes, static or time evolving, finding relevant and accurate patterns that can be used for predictive or descriptive modelling is impractical for human experts. In this paper, we concentrate our review on Swedish Administrative Health Registries (AHRs) and Electronic Health Records (EHRs) and provide an overview of recent and ongoing work in the area with focus on adverse drug events (ADEs) and heart failure.

Place, publisher, year, edition, pages
CEUR-WS.org , 2017.
Series
CEUR Workshop Proceedings, E-ISSN 1613-0073 ; 1960
National Category
Computer Sciences
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-149269OAI: oai:DiVA.org:su-149269DiVA, id: diva2:1159985
Conference
Second Workshop on Data Science for Social Good co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Dicovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18, 2017
Available from: 2017-11-24 Created: 2017-11-24 Last updated: 2022-02-28Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Free full text

Authority records

Rebane, JonathanKarlsson, IsakAsker, LarsBoström, HenrikPapapetrou, Panagiotis

Search in DiVA

By author/editor
Rebane, JonathanKarlsson, IsakAsker, LarsBoström, HenrikPapapetrou, Panagiotis
By organisation
Department of Computer and Systems Sciences
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 131 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf