van Diest P J, Belien J A, Baak J P
Institute for Pathology, Free University Hospital, Amsterdam, The Netherlands.
Pathol Res Pract. 1992 Jun;188(4-5):405-9. doi: 10.1016/S0344-0338(11)80027-0.
This article describes the set up of a rule-based expert system for histologic typing and grading of invasive breast cancer, which is designed to be a user-friendly tool that may be helpful for teaching and to support diagnosis making. The system raises questions and offers fixed choices to the user (usually yes/no) until a histologic diagnosis can be made with reasonable probability or enough data are available to assign a grade. As to histologic typing, the expert system is able to make the following diagnoses: ductal carcinoma, lobular carcinoma, medullary carcinoma, colloidal carcinoma, tubular carcinoma, and invasive cribriform carcinoma. If the diagnosis "ductal carcinoma" is arrived, the system offers the option to assign a histologic grade to the lesion. A first evaluation of the system in 30 cases (five each of the different subtypes) with unequivocal diagnoses by two human experts showed that the system classified 29 of the tumours in the same way as the human experts. The discrepancy case was solved after adding one rule to the system. Ten cases where a discrepancy existed between the original diagnosis of a referring centre and a reviewing human expert were all classified by the expert system in the same way as the human expert. The expert system thus seems to perform well. Further plans for evaluating, modifying and expanding the system are disclosed.
本文介绍了一种用于浸润性乳腺癌组织学分型和分级的基于规则的专家系统的建立，该系统旨在成为一个用户友好的工具，可能有助于教学并支持诊断决策。该系统向用户提出问题并提供固定选择（通常为是/否），直到能够以合理的概率做出组织学诊断或有足够的数据来确定分级。关于组织学分型，专家系统能够做出以下诊断：导管癌、小叶癌、髓样癌、胶样癌、管状癌和浸润性筛状癌。如果得出“导管癌”的诊断，系统会提供对病变进行组织学分级的选项。由两位人类专家对30例（每种不同亚型各5例）诊断明确的病例进行的系统首次评估表明，该系统对29例肿瘤的分类与人类专家相同。在向系统添加一条规则后，解决了存在差异的病例。在一个转诊中心的原始诊断与一位会诊人类专家之间存在差异的10例病例，专家系统的分类与人类专家完全相同。因此，该专家系统似乎表现良好。文中还披露了进一步评估、修改和扩展该系统的计划。
