Hamilton P W, Montironi R, Abmayr W, Bibbo M, Anderson N, Thompson D, Bartels P H
Department of Pathology, Queen's University of Belfast, Northern Ireland, UK.
Pathologica. 1995 Jun;87(3):237-45.
Bayesian belief networks (BBNs) are a novel tool for representing knowledge about diagnostic decision making and for obtaining a numerical measure of certainty in the final diagnosis. Belief networks have been applied to the pathological assessment of breast, prostate and skin lesions and have been shown to provide consistency in the grading of microscopic features and improve diagnosis. These applications are reviewed in the current paper. The application of BBNs has been further facilitated through the use of standardised imagery which is stored digitally and used to enter evidence into a BBN. It is predicted that the further development of BBNs with improved logical capabilities represent the key to improved decision making in pathology.
贝叶斯信念网络（BBNs）是一种用于表示诊断决策知识以及获得最终诊断中确定性数值度量的新型工具。信念网络已应用于乳腺、前列腺和皮肤病变的病理评估，并已证明能在微观特征分级方面提供一致性并改善诊断。本文对这些应用进行了综述。通过使用以数字方式存储并用于将证据输入贝叶斯信念网络的标准化图像，贝叶斯信念网络的应用得到了进一步推动。预计具有改进逻辑能力的贝叶斯信念网络的进一步发展是病理学中改善决策的关键。
