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Early screening diagnostic aid for heart disease using data mining: An evaluation using patient data that can be obtained without medical equipment
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2015 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Heart disease is the leading cause of death in the world. Being able to conduct an early screening diagnosis of heart disease at home, could potentially be a tool to reduce the amount of people who lose their lives to the disease in the future.

This report aims at investigating if an early screening diagnostic aid using no attributes requiring advanced medical equipment to be measured can be created, that acquires the same level of accuracy as previous data sets and studies. A litera- ture study of medical background, patient data sets and attributes, as well as data mining was conducted. A unique home data set consisting of attributes that can be obtained from home was created and data mining experiments were run in WEKA, using classification algorithms Naive-Bayes and Decision Trees.

The results are compared to the Cleveland data set in regards to accuracy. The study shows that the home data set does not deliver the same accuracy level as the Cleveland data set. The idea that similar accuracy can be obtained for the dierent sets has not been disproven and more exhaustive research is encouraged. 

Place, publisher, year, edition, pages
2015.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-166593OAI: oai:DiVA.org:kth-166593DiVA, id: diva2:811547
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Available from: 2015-05-12 Created: 2015-05-12 Last updated: 2022-06-23Bibliographically approved

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CiteExportLink to record
Permanent link

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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