SurviVIS: visual analytics for interactive survival analysis

Research output: Contribution to conferencePaper

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Abstract

The increasing quantity of data in biomedical informatics is leading towards better patient profiling and personalized medicine. Lab tests, medical images, and clinical data represent extraordinary sources for patient characterization. While retrospective studies focus on finding correlations in this sheer volume of data, potential new biomarkers are difficult to identify. A common approach is to observe patient mortality with respect to different clinical variables in what is called survival analysis. Kaplan-Meier plots, also known as survival curves, are generally used to examine patient survival in retrospective and prognostic studies. The plot is very intuitive and hence very popular in the medical domain to disclose evidence of poor or good prognosis. However, the Kaplan-Meier plots are mostly static and the data exploration of the plotted cohorts can be performed only with additional analysis. There is a need to make survival plots interactive and to integrate potential prognostic data that may reveal correlations with disease progression. We introduce SurviVIS, a visual analytics approach for interactive survival analysis and data integration on Kaplan-Meier plots. We demonstrate our work on a melanoma dataset and in the perspective of a potential use case in precision imaging.
Original languageEnglish
Pages73-77
Number of pages5
DOIs
Publication statusPublished - 2019
Event10th International EuroVis Workshop on Visual Analytics - Porto, Portugal
Duration: 3 Jun 20193 Jun 2019
https://www.eurova.org/eurova-2019

Conference

Conference10th International EuroVis Workshop on Visual Analytics
Abbreviated titleEuroVA 2019
CountryPortugal
CityPorto
Period3/06/193/06/19
Internet address

Fingerprint

Survival Analysis
Survival
Retrospective Studies
Precision Medicine
Informatics
Disease Progression
Melanoma
Biomarkers
Mortality

Cite this

Corvo, A., Garcia Caballero, H., & Westenberg, M. A. (2019). SurviVIS: visual analytics for interactive survival analysis. 73-77. Paper presented at 10th International EuroVis Workshop on Visual Analytics, Porto, Portugal. https://doi.org/10.2312/eurova.20191128
Corvo, Alberto ; Garcia Caballero, Humberto ; Westenberg, Michel A. / SurviVIS : visual analytics for interactive survival analysis. Paper presented at 10th International EuroVis Workshop on Visual Analytics, Porto, Portugal.5 p.
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abstract = "The increasing quantity of data in biomedical informatics is leading towards better patient profiling and personalized medicine. Lab tests, medical images, and clinical data represent extraordinary sources for patient characterization. While retrospective studies focus on finding correlations in this sheer volume of data, potential new biomarkers are difficult to identify. A common approach is to observe patient mortality with respect to different clinical variables in what is called survival analysis. Kaplan-Meier plots, also known as survival curves, are generally used to examine patient survival in retrospective and prognostic studies. The plot is very intuitive and hence very popular in the medical domain to disclose evidence of poor or good prognosis. However, the Kaplan-Meier plots are mostly static and the data exploration of the plotted cohorts can be performed only with additional analysis. There is a need to make survival plots interactive and to integrate potential prognostic data that may reveal correlations with disease progression. We introduce SurviVIS, a visual analytics approach for interactive survival analysis and data integration on Kaplan-Meier plots. We demonstrate our work on a melanoma dataset and in the perspective of a potential use case in precision imaging.",
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Corvo, A, Garcia Caballero, H & Westenberg, MA 2019, 'SurviVIS: visual analytics for interactive survival analysis', Paper presented at 10th International EuroVis Workshop on Visual Analytics, Porto, Portugal, 3/06/19 - 3/06/19 pp. 73-77. https://doi.org/10.2312/eurova.20191128

SurviVIS : visual analytics for interactive survival analysis. / Corvo, Alberto; Garcia Caballero, Humberto; Westenberg, Michel A.

2019. 73-77 Paper presented at 10th International EuroVis Workshop on Visual Analytics, Porto, Portugal.

Research output: Contribution to conferencePaper

TY - CONF

T1 - SurviVIS

T2 - visual analytics for interactive survival analysis

AU - Corvo, Alberto

AU - Garcia Caballero, Humberto

AU - Westenberg, Michel A.

PY - 2019

Y1 - 2019

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AB - The increasing quantity of data in biomedical informatics is leading towards better patient profiling and personalized medicine. Lab tests, medical images, and clinical data represent extraordinary sources for patient characterization. While retrospective studies focus on finding correlations in this sheer volume of data, potential new biomarkers are difficult to identify. A common approach is to observe patient mortality with respect to different clinical variables in what is called survival analysis. Kaplan-Meier plots, also known as survival curves, are generally used to examine patient survival in retrospective and prognostic studies. The plot is very intuitive and hence very popular in the medical domain to disclose evidence of poor or good prognosis. However, the Kaplan-Meier plots are mostly static and the data exploration of the plotted cohorts can be performed only with additional analysis. There is a need to make survival plots interactive and to integrate potential prognostic data that may reveal correlations with disease progression. We introduce SurviVIS, a visual analytics approach for interactive survival analysis and data integration on Kaplan-Meier plots. We demonstrate our work on a melanoma dataset and in the perspective of a potential use case in precision imaging.

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DO - 10.2312/eurova.20191128

M3 - Paper

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Corvo A, Garcia Caballero H, Westenberg MA. SurviVIS: visual analytics for interactive survival analysis. 2019. Paper presented at 10th International EuroVis Workshop on Visual Analytics, Porto, Portugal. https://doi.org/10.2312/eurova.20191128