Cristin-resultat-ID: 1356423
Sist endret: 27. mai 2018 16:50
NVI-rapporteringsår: 2016
Resultat
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
2016

Visual Exploration and Cohort Identification of Acute Patient Histories Aggregated from Heterogeneous Sources

Bidragsytere:
  • Rune Sætre
  • Øystein Nytrø
  • Stein Jakob Nordbø og
  • Aslak Steinsbekk

Bok

2016 IEEE 32nd International Conference on Data Engineering Workshops
ISBN:
  • 978-1-5090-2109-3

Utgiver

IEEE
NVI-nivå 1

Serie

Proceedings - International Conference on Data Engineering
ISSN 1084-4627
e-ISSN 1084-4627
NVI-nivå 2

Om resultatet

Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
Publiseringsår: 2016
Volum: 32
Hefte: 2
Sider: 71 - 77
ISBN:
  • 978-1-5090-2109-3
Open Access

Klassifisering

HRCS

  • Helsekategori: 20 - Generell helserelevans
    Aktivitet: 8.1 - Organisering og levering av tjenester

Fagfelt (NPI)

Fagfelt: Informatikk og datateknikk
- Fagområde: Realfag og teknologi

Beskrivelse Beskrivelse

Tittel

Visual Exploration and Cohort Identification of Acute Patient Histories Aggregated from Heterogeneous Sources

Sammendrag

How can we use information visualization to support retrospective, exploratory analysis of collections of histories for patients admitted to acute care? This paper describes a novel design for visual cohort identification and exploration. We have developed a tool that integrates multiple, heterogeneous clinical data sources and allows alignment, querying and abstraction in a common workbench. This paper presents results from two projects and a review of related work in the field of information visualization including both presentation and interactive navigation of the information. We have developed an interactive prototype and present the visualization aspect of this prototype and a brief demonstration of its use in a research project with a large cohort of patients. The prototype represents and reasons with patient events in different OWL-formalizations according to the perspective and use: One for integration and alignment of patient records and observations; Another for visual presentation of individual or cohort trajectories. Health researchers have successfully analyzed large cohorts (over 100,000 individuals) using the tool. We have also used the tool to produce interactive personal health time-lines (for more than 10,000 individuals) on the web. Utility, usability and effect have been tested extensively and the results so far are promising. We envision that clinicians who want to learn more about groups of patients and their treatment processes will find the tool valuable. In addition, we believe that the visualization can be useful to researchers looking at data to be statistically evaluated, in order to discover new hypotheses or get ideas for the best analysis strategies. Our main conclusion is that the tool is usable, but it can be challenging to use for large data sets.

Bidragsytere

Aktiv cristin-person

Rune Sætre

  • Tilknyttet:
    Forfatter
    ved Institutt for datateknologi og informatikk ved Norges teknisk-naturvitenskapelige universitet
Aktiv cristin-person

Øystein Nytrø

  • Tilknyttet:
    Forfatter
    ved Institutt for datateknologi og informatikk ved Norges teknisk-naturvitenskapelige universitet

Stein Jakob Nordbø

  • Tilknyttet:
    Forfatter
    ved Andre institusjoner
Aktiv cristin-person

Aslak Steinsbekk

  • Tilknyttet:
    Forfatter
    ved Institutt for samfunnsmedisin og sykepleie ved Norges teknisk-naturvitenskapelige universitet
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Resultatet er en del av Resultatet er en del av

2016 IEEE 32nd International Conference on Data Engineering Workshops.

IEEE, ICDE. 2016, IEEE. Vitenskapelig antologi/Konferanseserie
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