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Patient data representation for outcome prediction of congestive heart failure patients
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Artificial Intelligence (AI) has its roots in every field in present scenario. Healthcare is one of the sectors where AI is reaching considerable growth in recent years. Tremendous increase in healthcare data availability and considerable growth in big data analytic methods has paved way for success of AI in healthcare and research is being driven towards improvement in quality of service. Healthcare data is stored in the form of Electronic Health Records (EHR) which consists of temporally ordered patient information. There are many challenges with EHR data like heterogeneity, missing values, biases, noise, temporality etc. This master thesis focuses on addressing the problem of visit level irregularity which refers to irregular timing between events (patient’s visits).

Place, publisher, year, edition, pages
2019.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-40818OAI: oai:DiVA.org:hh-40818DiVA, id: diva2:1366556
Subject / course
Computer science and engineering
Educational program
Master's Programme in Embedded and Intelligent Systems, 120 credits
Presentation
2019-09-10, 13:15 (English)
Supervisors
Examiners
Available from: 2019-10-30 Created: 2019-10-29 Last updated: 2019-10-30Bibliographically approved

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fulltext(6187 kB)28 downloads
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File name FULLTEXT02.pdfFile size 6187 kBChecksum SHA-512
355c18a36ee435e2618379d34a09ad313ed01a258ab7735877766f3aa4343ac29c63d70f787ddaffca1f75d6e1f7ac6a80ef09ee830bda67cdced17c93c81ecb
Type fulltextMimetype application/pdf

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CAISR - Center for Applied Intelligent Systems Research
Engineering and Technology

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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