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Artificial intelligence and Machine learning: a diabetic readmission study
Kristianstad University, Faculty of Natural Science, Avdelningen för datavetenskap. (Fakulteten för naturvetenskap)
Kristianstad University, Faculty of Natural Science, Avdelningen för datavetenskap.
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The maturing of Artificial intelligence provides great opportunities for healthcare, but also comes with new challenges. For Artificial intelligence to be adequate a comprehensive analysis of the data is necessary along with testing the data in multiple algorithms to determine which algorithm is appropriate to use. In this study collection of data has been gathered that consists of patients who have either been readmitted or not readmitted to hospital within 30-days after being admitted. The data has then been analyzed and compared in different algorithms to determine the most appropriate algorithm to use.

Place, publisher, year, edition, pages
2019. , p. 37
Keywords [en]
Artificial intelligence, Machine learning, Logistic regression, K-nearest neighbor, Boosted decision tree, Artificial neural network
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hkr:diva-19412OAI: oai:DiVA.org:hkr-19412DiVA, id: diva2:1323754
Educational program
Bachelor programme in Computer Software Development
Presentation
2019-06-05, 17:02 (English)
Supervisors
Examiners
Available from: 2019-06-13 Created: 2019-06-12 Last updated: 2019-06-13Bibliographically approved

Open Access in DiVA

fulltext(954 kB)80 downloads
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Type fulltextMimetype application/pdf

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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