Competitive Analysis about Online Problem of Kidney Transplantation Acceptance Decision-Making

王嘉寅 1; 许晓雯 2

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Competitive Analysis about Online Problem of Kidney Transplantation Acceptance Decision-Making

更新时间：2025-12-08

- Competitive Analysis about Online Problem of Kidney Transplantation Acceptance Decision-Making
- Vol. 42, Issue 4, Pages: 423-426(2008)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP312
- Online First：10 April 2008，
  
  Published：2008
- 稿件说明：
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王嘉寅 1, 许晓雯 2. Competitive Analysis about Online Problem of Kidney Transplantation Acceptance Decision-Making[J]. 2008, 42(4): 423-426.
DOI：

王嘉寅 1, 许晓雯 2. Competitive Analysis about Online Problem of Kidney Transplantation Acceptance Decision-Making[J]. 2008, 42(4): 423-426. DOI：

摘要

通过研究肾疾病患者在仅掌握当前和之前治疗信息时

是否接受肾移植的决策问题

提出了一种局内肾移植接受决策问题的竞争分析方法.首先将肾疾病患者分为可以治愈和无法治愈2类

并对此分别提出了继续接受治疗或接受肾移植、立即接受肾移植或等待更合适的肾资源的2种局内决策算法

前者考虑、比较了累计治疗费用与移植费用

后者比较了2次移植机会之间的治疗费用与免疫费用的改进额度

同时为肾疾病可以治愈的患者确立了局内算法集合.在竞争分析中引入了风险补偿模型

以评价局内算法的改进比率.竞争分析显示

所提局内算法的决策所带来的费用与局外算法带来的费用之比小于2

患者可根据自身对疾病的治愈预期和风险容忍度选择使用算法

以获得对应的补偿收益

从而达到治疗费用最小化的目的.

Abstract

The decision-making of the kidney transplantation acceptance is studied and a competitive analysis method is proposed

when only the current and previous treatment information is held by patients. Patients are recognized as curable and incurable

and two online algorithms for these two kinds of patients are proposed. The first algorithm concerns with either continuing the treatment or accepting kidney transplantation by considering and comparing the total treatment spending and the transplantation cost

while the second one concerns with either waiting for more suitable kidney resource or accepting transplantation immediately by comparing the treatment spending between two transplantation chances and improvement quantum of immunity cost after transplantation operation. Then the set of online algorithms for curable patients are presented. These online algorithms are evaluated by introducing a risk reward model into the competitive analysis. Results show that the ratio of the spendings caused by both the online algorithms and the offline algorithms are less than 2. Patients can choose online algorithms by their own treatment expects and risk tolerance to obtain corresponding risk compensation with a minimum treatment spending.

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references

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ER Xiujiang, XIE Zelin, DU Lindong, et al. The early rejection and HLA-A,B,DR mismatching of kidney transplantation [J]. Journal of Clinical and Experimental Medicine, 2004, 3(4):197-199.

朱志军,徐寅峰,徐维军.局内租赁问题的风险补偿模型及其竞争分析[J].管理科学学报,2004,7(3):64-68.

ZHU Zhijun, XU Yinfeng, XU Weijun. Risk-reward model of online leasing problem and its competitive analysis [J]. Journal of Management Sciences in China, 2004,7(3):64-68.

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