Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Classifying the Severity of an Acute Coronary Syndrome by Mining Patient Data
Vise andre og tillknytning
Ansvarlig organisasjon
2009 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert) Published
Abstract [en]

An Acute Coronary Syndrome (ACS) is a set of clinical signs and symptoms, interpreted as the result of cardiac ischemia, or abruptly decreased blood flow to the heart muscle. The subtypes of ACS include Unstable Angina (UA) and Myocardial Infarction (MI). Acute MI is the single most common cause of death for both men and women in the developed world. Several data mining studies have analyzed different types of patient data in order to generate models that are able to predict the severity of an ACS. Such models could be used as a basis for choosing an appropriate form of treatment. In most cases, the data is based on electrocardiograms (ECGs). In this preliminary study, we analyze a unique ACS database, featuring 28 variables, including: chronic conditions, risk factors, and laboratory results as well as classifications into MI and UA. We evaluate different types of feature selection and apply supervised learning algorithms to a subset of the data. The experimental results are promising, indicating that this type of data could indeed be used to generate accurate models for ACS severity prediction.

sted, utgiver, år, opplag, sider
Linköping: Linköping University Electronic Press , 2009.
Emneord [en]
acute coronary syndrome, acs, myocardial infarction, unstable angina, diagnosis, severity, data mining, classification
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-8097Lokal ID: oai:bth.se:forskinfoF5989732418652ECC12575C4005865F7OAI: oai:DiVA.org:bth-8097DiVA, id: diva2:835784
Konferanse
25th Annual Workshop of the Swedish Artificial Intelligence Society
Tilgjengelig fra: 2012-09-18 Laget: 2009-05-28 Sist oppdatert: 2018-01-11bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Personposter BETA

Lavesson, Niklas

Søk i DiVA

Av forfatter/redaktør
Lavesson, Niklas

Søk utenfor DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric

urn-nbn
Totalt: 116 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf