FLAS: Fuzzy lung allocation system for US-based transplantations

This paper presents a fuzzy lung allocation system (FLAS) in order to determine which potential recipients would receive a lung for transplantation when it becomes available in the USA. The developed system deals with the vagueness and fuzziness of the decision making of the medical experts in order to achieve accurate lung allocation processes in terms of transplant survival time and functional status after transplantation. The proposed approach is based on a real data set from the United Network for Organ Sharing (UNOS) to investigate how well it mimics the experience of transplant physicians in the field of lung allocation. The results are very promising in terms of both prediction accuracy (with an R2 value of 83.2 percent and an overall accuracy of 82.1 percent) along with better interpretation capabilities and hence are superior to the existing techniques in literature. Furthermore, the proposed decision process provides a more effective (i.e. accurate), time-efficient, and systematic decision support tool for this problem with two criteria being considered i.e. graft survival time and functional status after transplantation.