Classification of left heart functional dimensions by clustering cardiac Echo-Doppler measurements

Roni Ben Ishay, Scharf Shimon, Chaim Yosefy, Maya Herman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cardiac Echo-Doppler (Echo) data may contain hidden information that cannot be revealed and identified by an experienced cardiologist. Thus, important relations between Cardiac dimensions (CD) may be misinterpreted. Clustering is commonly used in Data Mining (DM) and aimed to partition data into clusters. The aim of this work was to find possible correlations between CD in order to upgrade and improve diagnostic abilities. This relation was already proved for homogenous populations (and known mechanism) of diseases such as Hypertension. In contrast, in our work the population was heterogeneous (normal and various diseases) with no known mechanism (such as Hypertension). Therefore, clustering algorithms such as K-means (KM), Kohonen (Koh) and TwoStep (TS) were applied on 24,400 data objects of Cardiac Echo measurements. The commercial DM tool Clementine (Clem) was used. Each algorithm generated different clusters. Despite this, between left atrial Area (LA_Area) and ascending aortic Diameter (AsAo_Dia), pathological correlations were identified.

Original languageEnglish
Title of host publicationITRE 2006 - 4th International Conference on Information Technology
Subtitle of host publicationResearch and Education, Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Pages121-125
Number of pages5
ISBN (Print)1424408598, 9781424408597
DOIs
StatePublished - 1 Jan 2006
EventITRE 2006 - 4th International Conference on Information Technology: Research and Education - Tel-Aviv, Israel
Duration: 17 Oct 200618 Oct 2006

Publication series

NameITRE 2006 - 4th International Conference on Information Technology: Research and Education, Proceedings

Conference

ConferenceITRE 2006 - 4th International Conference on Information Technology: Research and Education
Country/TerritoryIsrael
CityTel-Aviv
Period17/10/0618/10/06

Keywords

  • Ascending aorta
  • Cardiac dimensions
  • Clustering
  • Data mining

ASJC Scopus subject areas

  • Computer Science (all)
  • Information Systems
  • Information Systems and Management

Fingerprint

Dive into the research topics of 'Classification of left heart functional dimensions by clustering cardiac Echo-Doppler measurements'. Together they form a unique fingerprint.

Cite this