{"id":{"repo_id":"ohiolink","oai_identifier":"oai:etd.ohiolink.edu:toledo1345153510"},"canonical_url":"https://search.dev.ndltd.org/etd/ohiolink/oai:etd.ohiolink.edu:toledo1345153510","repository":{"repo_id":"ohiolink","name":"OhioLINK","base_url":"https://etd.ohiolink.edu/acprod/odb_etd/ws/oai/oai"},"display":{"title":"Kidney Compatibility Score Generation for a Donor - Recipient pair using Fuzzy Logic","abstract":"This thesis, proposes and implements a Fuzzy Logic based Hierarchical model to address the problem of filtering the donor recipient pairs by predicting a kidney compatibility score. Donor – Recipient pair incompatibility is one of the major problems encountered in Renal Transplantation. Kidney Paired Donation is a barter system where the pairs exchange the donor organs to overcome the disadvantage of incompatibility. Identification of such pairs requires a Kidney Transplant Surgeon to evaluate the compatibility of swapped pairs. Unfortunately, such incompatible pairs run into huge numbers which is a herculean task for a surgeon and can prone to human fatigue.This work presents a Hierarchical System developed based on Fuzzy Logic to determine the quality of a Kidney Transplant based on various input parameters. A surgeon’s expertise in selecting the incompatible pairs is captured and embedded in this model in the form of rules. Fuzzy membership functions are designed to reflect the characteristics of input parameters. This model has been tested on several data sets. The pairs selected based on the kidney compatibility scores matched with the surgeon’s choice in most of the cases. This application provides many options to explore in future.","abstract_html":"This thesis, proposes and implements a Fuzzy Logic based Hierarchical model to address the problem of filtering the donor recipient pairs by predicting a kidney compatibility score. Donor – Recipient pair incompatibility is one of the major problems encountered in Renal Transplantation. Kidney Paired Donation is a barter system where the pairs exchange the donor organs to overcome the disadvantage of incompatibility. Identification of such pairs requires a Kidney Transplant Surgeon to evaluate the compatibility of swapped pairs. Unfortunately, such incompatible pairs run into huge numbers which is a herculean task for a surgeon and can prone to human fatigue.This work presents a Hierarchical System developed based on Fuzzy Logic to determine the quality of a Kidney Transplant based on various input parameters. A surgeon’s expertise in selecting the incompatible pairs is captured and embedded in this model in the form of rules. Fuzzy membership functions are designed to reflect the characteristics of input parameters. This model has been tested on several data sets. The pairs selected based on the kidney compatibility scores matched with the surgeon’s choice in most of the cases. This application provides many options to explore in future.","abstract_has_math":false,"creators":["Yellanki, Sampath Kumar"],"institution":"University of Toledo","degree_name":"Master of Science in Engineering","degree_level":"masters","degree_discipline":"College of Engineering","degree_department":null,"school":null,"contributors":["Kaur, Devinder"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-24T03:36:08Z","subjects":["Artificial Intelligence","Paired Kidney Donation","Fuzzy Logic","Combs Method","Kidney Incompatibility","Kidney Compatibility Score","Rule Explosion"],"languages":["English"],"rights":["unrestricted","This thesis or dissertation is protected by copyright: all rights reserved. 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Unfortunately, such incompatible pairs run into huge numbers which is a herculean task for a surgeon and can prone to human fatigue.This work presents a Hierarchical System developed based on Fuzzy Logic to determine the quality of a Kidney Transplant based on various input parameters. A surgeon’s expertise in selecting the incompatible pairs is captured and embedded in this model in the form of rules. Fuzzy membership functions are designed to reflect the characteristics of input parameters. This model has been tested on several data sets. The pairs selected based on the kidney compatibility scores matched with the surgeon’s choice in most of the cases. This application provides many options to explore in future."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf","p.133","1.49 MB"]},{"key":"dc:title","label":"Title","values":["Kidney Compatibility Score Generation for a Donor - Recipient pair using Fuzzy Logic"]}]}],"canonical_facts":{"dc:contributor":["Kaur, Devinder"],"dc:creator":["Yellanki, Sampath Kumar"],"dc:date":["2012"],"dc:description":["This thesis, proposes and implements a Fuzzy Logic based Hierarchical model to address the problem of filtering the donor recipient pairs by predicting a kidney compatibility score. Donor – Recipient pair incompatibility is one of the major problems encountered in Renal Transplantation. Kidney Paired Donation is a barter system where the pairs exchange the donor organs to overcome the disadvantage of incompatibility. Identification of such pairs requires a Kidney Transplant Surgeon to evaluate the compatibility of swapped pairs. Unfortunately, such incompatible pairs run into huge numbers which is a herculean task for a surgeon and can prone to human fatigue.This work presents a Hierarchical System developed based on Fuzzy Logic to determine the quality of a Kidney Transplant based on various input parameters. A surgeon’s expertise in selecting the incompatible pairs is captured and embedded in this model in the form of rules. Fuzzy membership functions are designed to reflect the characteristics of input parameters. This model has been tested on several data sets. The pairs selected based on the kidney compatibility scores matched with the surgeon’s choice in most of the cases. 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