Kidney Allocation Expert System with Case-Based Reasoning
Kidney Allocation Expert System with Case-Based Reasoning
复制标题
基于案例推理的肾脏分配专家系统
DOI：
10.1007/978-3-540-30198-1_50
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
E. Yilmaz
中科院分区：
文献类型：
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作者：
T. Yakhno;Cansin Yilmaz;S. Gülseçen;E. Yilmaz
器官移植领域的专家必须根据医学、社会、道德和伦理因素作出关键决定。本文介绍了肾脏分配专家系统KARES-CBR。我们的系统由两个主要部分组成。传统的专家系统部分使用基于规则的知识。这些规则包含一般医学知识，如血型和抗原匹配规则。另一组规则包含与器官移植的社会和伦理信息相关的决策规则。在做出决定之后，专家系统组件生成医学上适合移植可用器官的患者的列表。
该系统的另一部分收集以前成功的器官移植病例的档案。这些历史数据用于系统的基于案例的推理部分。使用不同的度量，系统计算所选患者的肾移植相对于先前成功移植的相似性值。因此，它选择了最合适的病人进行器官移植。该系统被实现为一个专家系统外壳和不同的标准和参数可以很容易地修改。该系统在大学医院的真实的数据上进行了测试。
Experts in fields of organ transplantation have to make crucial decisions based on medical, social, moral and ethical factors. The paper describes the kidney allocation expert system KARES-CBR. Our system consists of two main components. Traditional expert system part uses rule-based knowledge. These rules contain general medical knowledge, such as blood group and antigens matching rules. Another group of rules contains decision making rules related to social and ethical information about organ transplantation. After decision making, the expert system component generates the list of medically suitable patients for the transplantation of an available organ.
Another part of the system collects the archive of previous successful organ transplantation cases. This historical data are used in case-based reasoning part of the system. Using different metrics, the system calculates the similarity values for kidney transplantation of selected patients relative to the previous successful transplantations. As a result, it selects the best suitable patient for organ transplantation. The system is implemented as an expert system shell and the different criteria and parameters can be easily modified. The system was tested on real data in the University hospital.