Visual analytics for congestive heart failure mortality prediction

Rema Padman, Ofir Ben-Assuli, Tsipi Heart, Nir Shlomo, Robert Klempfner

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


Several indices exist to classify Congestive Heart Failure (CHF) patients' propensity for early mortality; however, they are primarily based on limited data and are not intuitive to use at the point of care. We investigate a novel, data-driven, risk assessment and visualization approach to investigate mortality prediction of CHF patients using data retrieved from an intensively digitized hospital's data repository. Combining well-known, computationally efficient, dimensionality reduction (DR) methods with 2-d information visualization, the method classifies and visualizes CHF patients into high and low risk groups, contextualized by the factors driving their classification. The DR method performed similar to logistic regression (LR), but visualized the classification and its significant factors at the population level, individual level and the potential impact of interventions for an individual patient. These are encouraging results in favor of the proposed visualization approach, and contributes to the current focus on advancing patient care via large-scale visual analytics.

Original languageEnglish
Title of host publicationMEDINFO 2019
Subtitle of host publicationHealth and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics
EditorsBrigitte Seroussi, Lucila Ohno-Machado, Lucila Ohno-Machado, Brigitte Seroussi
PublisherIOS Press
Number of pages5
ISBN (Electronic)9781643680026
StatePublished - 21 Aug 2019
Externally publishedYes
Event17th World Congress on Medical and Health Informatics, MEDINFO 2019 - Lyon, France
Duration: 25 Aug 201930 Aug 2019

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Conference17th World Congress on Medical and Health Informatics, MEDINFO 2019


  • Computer graphics
  • Heart failure
  • Risk assessment

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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