Jamieson P W
Department of Neurology, University of Kansas Medical Center, Kansas City 66103.
Comput Biomed Res. 1991 Aug;24(4):307-20. doi: 10.1016/0010-4809(91)90031-q.
The ability to diagnose multiple interacting disorders and explain them in a coherent causal framework has only partially been achieved in medical expert systems. This paper proposes a causal model for diagnosing and explaining multiple disorders whose key elements are: physician-directed hypotheses generation, object-oriented knowledge representation, and novel explanation heuristics. The heuristics modify and link the explanations to make the physician aware of diagnostic complexities. A computer program incorporating the model currently is in use for diagnosing peripheral nerve and muscle disorders. The program successfully diagnoses and explains interactions between diseases in terms of underlying pathophysiologic concepts. The model offers a new architecture for medical domains where reasoning from first principles is difficult but explanation of disease interactions is crucial for the system's operation.
医学专家系统仅部分实现了诊断多种相互作用的病症并在连贯的因果框架中对其进行解释的能力。本文提出了一种用于诊断和解释多种病症的因果模型，其关键要素包括：由医生指导生成假设、面向对象的知识表示以及新颖的解释启发式方法。这些启发式方法修改并关联解释，以使医生意识到诊断的复杂性。目前，一个包含该模型的计算机程序正在用于诊断周围神经和肌肉疾病。该程序根据潜在的病理生理概念成功诊断并解释了疾病之间的相互作用。该模型为医学领域提供了一种新的架构，在这些领域中，从第一原理进行推理很困难，但疾病相互作用的解释对于系统的运行至关重要。
