Graham A R, Paplanus S H, Bartels P H
Department of Pathology, University of Arizona Health Sciences Center, Tucson 85724.
Am J Clin Pathol. 1990 Oct;94(4 Suppl 1):S15-8.
The diagnostic expert system for colonic lesions (DESCL) was designed to discriminate colonic adenoma and adenocarcinoma from normal colonic tissue. Although it was originally developed for use in conjunction with a machine vision analytic system, the DESCL has evolved into a teaching tool and a model for conceptual machine learning. The expert system is table driven and consists of a shell and a knowledge base. The latter comprises a series of architectural and cytologic observations and a quantitative estimate of diagnostic importance relating these observations to diagnostic outcome. In a validation study of 100 colonic lesions, the expert system achieved a success rate of 98%. It has the flexibility to allow individual pathologists to "customize" the knowledge base to suit their diagnostic criteria.
结肠病变诊断专家系统（DESCL）旨在从正常结肠组织中鉴别出结肠腺瘤和腺癌。尽管它最初是为与机器视觉分析系统结合使用而开发的，但DESCL已发展成为一种教学工具和概念性机器学习模型。该专家系统由表格驱动，由一个外壳和一个知识库组成。知识库包含一系列结构和细胞学观察结果，以及将这些观察结果与诊断结果相关联的诊断重要性的定量估计。在一项对100个结肠病变的验证研究中，该专家系统的成功率达到了98%。它具有灵活性，允许个体病理学家根据自己的诊断标准“定制”知识库。
