Applying Metalevel Argumentation Frameworks to Support Medical Decision Making
Applying Metalevel Argumentation Frameworks to Support Medical Decision Making
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DOI：
10.1109/mis.2021.3051420
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发表时间：
2021-03-01
影响因子：
6.4
通讯作者：
Parsons, Simon
中科院分区：
文献类型：
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作者：
Kokciyan, Nadin;Sassoon, Isabel;Parsons, Simon
人们越来越多地使用人工智能作为决策支持系统（DSS）的基础，以帮助他们做出明智的决策。如果决策支持系统缺乏支持或证据来证明其建议的合理性，则采用决策支持系统具有挑战性。DSS被广泛应用于医疗领域，由于该领域的复杂性和大量的数据，使人工处理困难。本文提出了一个基于元级论证的决策支持系统，它可以对异构数据进行推理（例如，身体测量、电子健康记录、临床指南），同时结合这些决定的人类受益者的偏好。系统为它提出的建议构造基于模板的解释。建议的框架已在一个系统中实施，以支持中风患者，其功能已在试点研究中进行了测试。用户反馈表明，该系统可以在较长时间内有效运行。
People are increasingly employing artificial intelligence as the basis for decision-support systems (DSSs) to assist them in making well-informed decisions. Adoption of DSS is challenging when such systems lack support, or evidence, for justifying their recommendations. DSSs are widely applied in the medical domain, due to the complexity of the domain and the sheer volume of data that render manual processing difficult. This article proposes a metalevel argumentation-based decision-support system that can reason with heterogeneous data (e.g., body measurements, electronic health records, clinical guidelines), while incorporating the preferences of the human beneficiaries of those decisions. The system constructs template-based explanations for the recommendations that it makes. The proposed framework has been implemented in a system to support stroke patients and its functionality has been tested in a pilot study. User feedback shows that the system can run effectively over an extended period.