engleski

Interactive Visual Analysis of Intensive Care Unit Data - Relationship between Serum Sodium Concentration, its Rate of Change and Survival Outcome

In this paper we present a case study of interactive visual analysis and exploration of a large ICU data set. The data consists of patients’ records containing scalar data representing various patients’ parameters (e.g. gender, age, weight), and time series data describing logged parameters over time (e.g. heart rate, blood pressure). Due to the size and complexity of the data, coupled with limited time and resources, such ICU data is often not utilized to its full potential, although its analysis could contribute to a better understanding of physiological, pathological and therapeutic processes, and consequently lead to a improvement of medical care. During the exploration of this data we identified several analysis tasks and adapted and improved a coordinated multiple views system accordingly. Besides a curve view which also supports time series with gaps, we introduced a summary view which allows an easy comparison of subsets of the data and a box plot view in a coordinated multiple views setup. Furthermore, we introduced an inverse brush, a secondary brush which automatically selects non-brushed items, and updates itself accordingly when the original brush is modified. The case study describes how we used the system to analyze data from 1447 patients from the ICU at Guy’s & St. Thomas’ NHS Foundation Trust in London. We were interested in the relationship between serum sodium concentration, its rate of change and their effect on ICU mortality rates. The interactive visual analysis led us to findings which were fascinating for medical experts, and which would be very difficult to discover using conventional analysis methods usually applied in the medical field. The overall feedback from domain experts (coauthors of the paper) is very positive.

Coordinated Multiple Views, Intensive Care Unit Data, Interactive Visual Analysis

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