Literature DB >> 16378053

Fuzzy organ allocation system for cadaveric kidney transplantation.

Emin Gundogar1, Fatih M Duran, Yavuz B Canbolat, Aydin Turkmen.   

Abstract

BACKGROUND: The recipient selection decision for a cadaveric donor kidney is complex and based on multiple criteria, not only medical but also ethical and political criteria.
METHODS: In this study, we develop the Fuzzy Organ Allocation System (FORAS) to determine who among potential recipients receives a cadaveric kidney when it becomes available. FORAS balances various kidney allocation objectives and deals with the ambiguity and fuzziness in the allocation process.
RESULTS: We used simulation to investigate how well FORAS represents the thinking of a transplant physician with regard to kidney allocation. We also compared FORAS with the United Network for Organ Sharing (UNOS) scoring system and the Turkish National Coordination for Organ Transplant (TONKS) algorithm used in Turkey. We found that FORAS well represents expert thinking in kidney allocation.
CONCLUSIONS: A simulated kidney allocation experiment based on real patient and donor data showed that FORAS is more useful than other kidney allocation systems because its results more closely reflect the thinking of experienced transplant physicians.

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Year:  2005        PMID: 16378053     DOI: 10.1097/01.tp.0000183287.04630.05

Source DB:  PubMed          Journal:  Transplantation        ISSN: 0041-1337            Impact factor:   4.939


  3 in total

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Authors:  Amir Elalouf
Journal:  Int J Environ Res Public Health       Date:  2022-06-06       Impact factor: 4.614

2.  Ranking patients on the kidney transplant waiting list based on fuzzy inference system.

Authors:  Nasrin Taherkhani; Mohammad Mehdi Sepehri; Roghaye Khasha; Shadi Shafaghi
Journal:  BMC Nephrol       Date:  2022-01-15       Impact factor: 2.388

3.  Identification and weighting of kidney allocation criteria: a novel multi-expert fuzzy method.

Authors:  Nasrin Taherkhani; Mohammad Mehdi Sepehri; Shadi Shafaghi; Toktam Khatibi
Journal:  BMC Med Inform Decis Mak       Date:  2019-09-06       Impact factor: 2.796

  3 in total

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