An Agent Supporting Symptom Elicitation in Physician-Patient Dialogue

Marco Lanciotti, C. Escazut, C. Pereira, Claudio Sartori, Emanuele Galasso
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引用次数: 0

Abstract

The main objective of the framework we are proposing is to help the physician obtain information about the patient’s condition in order to reach the correct diagnosis as soon as possible. In our proposal, the number of interactions between the physician and the patient is reduced to a strict minimum on the one hand and, on the other hand, it is made possible to increase the number of questions to be asked if the uncertainty about the diagnosis persists. These advantages are due to the fact that (i) we implement a reasoning component that allows us to predict a symptom from another symptom without explicitly asking the patient, (ii) we consider non-binary values for the weights associated to the symptoms, and (iii) we introduce a dataset filtering process in order to choose which partition should be used with respect to some particular characteristics of the patient The experimental results we obtained are very encouraging.
在医患对话中支持症状激发的代理
我们提出的框架的主要目标是帮助医生获得有关患者病情的信息,以便尽快做出正确的诊断。在我们的建议中,医生和病人之间的互动数量一方面被严格减少到最低限度,另一方面,如果诊断的不确定性持续存在,就有可能增加要问的问题的数量。这些优势是由于(i)我们实现了一个推理组件,使我们能够在不明确询问患者的情况下从另一个症状中预测一个症状,(ii)我们考虑了与症状相关的权重的非二进制值,以及(iii)我们引入了一个数据集过滤过程,以便根据患者的某些特定特征选择应该使用哪个分区。我们获得的实验结果非常令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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