A data science approach for quantifying spatio-temporal effects to graft failures in organ transplantation

Diego Pinheiro, Farag Hamad, Martin Cadeiras, Ronaldo Menezes, Nezamoddin Nezamoddini-Kachouie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The transplantation of solid organs is one of the most important accomplishments of modern medicine. Yet, organ shortage is a major public health issue; 8,000 people died while waiting for an organ in 2014. Meanwhile, the allocation system currently implemented can lead to organs being discarded and the medical community still investigates factors that affects early graft failure such as distance and ischemic time. In this paper, we investigate early graft failure under a spatio-temporal perspective using a data science unified approach for all six organs that is based on complementary cumulative analysis of both distance and ischemic time. Interestingly, although distance seems to highly affect some organs (e.g. liver), it appears to have no effect on others (e.g. kidney). Similarly, the results on ischemic time confirm it affects early graft failure with higher influence for some organs such as (e.g. heart) and lower influence for others such as (e.g. kidney). This poses the question whether the allocation policies should be individually designed for each organ in order to account for their particularities as shown in this work.

Original languageEnglish (US)
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3433-3436
Number of pages4
ISBN (Electronic)9781457702204
DOIs
StatePublished - Oct 13 2016
Externally publishedYes
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: Aug 16 2016Aug 20 2016

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2016-October
ISSN (Print)1557-170X

Conference

Conference38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
CountryUnited States
CityOrlando
Period8/16/168/20/16

Fingerprint

Transplantation (surgical)
Organ Transplantation
Grafts
Transplants
Public health
Kidney
Liver
Modern 1601-history
Medicine
Public Health

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Pinheiro, D., Hamad, F., Cadeiras, M., Menezes, R., & Nezamoddini-Kachouie, N. (2016). A data science approach for quantifying spatio-temporal effects to graft failures in organ transplantation. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 (pp. 3433-3436). [7591466] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2016-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2016.7591466

A data science approach for quantifying spatio-temporal effects to graft failures in organ transplantation. / Pinheiro, Diego; Hamad, Farag; Cadeiras, Martin; Menezes, Ronaldo; Nezamoddini-Kachouie, Nezamoddin.

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 3433-3436 7591466 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2016-October).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pinheiro, D, Hamad, F, Cadeiras, M, Menezes, R & Nezamoddini-Kachouie, N 2016, A data science approach for quantifying spatio-temporal effects to graft failures in organ transplantation. in 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016., 7591466, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2016-October, Institute of Electrical and Electronics Engineers Inc., pp. 3433-3436, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, Orlando, United States, 8/16/16. https://doi.org/10.1109/EMBC.2016.7591466
Pinheiro D, Hamad F, Cadeiras M, Menezes R, Nezamoddini-Kachouie N. A data science approach for quantifying spatio-temporal effects to graft failures in organ transplantation. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 3433-3436. 7591466. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2016.7591466
Pinheiro, Diego ; Hamad, Farag ; Cadeiras, Martin ; Menezes, Ronaldo ; Nezamoddini-Kachouie, Nezamoddin. / A data science approach for quantifying spatio-temporal effects to graft failures in organ transplantation. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 3433-3436 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).
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