Argumentation for explainable reasoning with conflicting medical recommendations
Kristijonas Čyras, Brendan C. Delaney, Denys Prociuk, Francesca Toni, Martin D. Chapman, Jesús Domínguez, Vasa Ćurčin · Spiral (Imperial College London) · 2018
Designing a treatment path for a patient suffering from multiple conditions involves merging and applying multiple clinical guidelines and is recognised as a difficult task. This is especially relevant in the treatment of patients with multiple chronic diseases, such as chronic obstructive pulmonary disease, because of the high risk of any treatment change having potentially lethal exacerbations. Clinical guidelines are typically designed to assist a clinician in treating a single condition with no general method for integrating them. Additionally, guidelines for different conditions may contain mutually conflicting recommendations with certain actions potentially leading to adverse effects. Finally, individual patient preferences need to be respected when making decisions. In this work we present a description of an integrated framework and a system to execute conflicting clinical guideline recommendations by taking into account patient specific information and preferences of various parties. Overall, our framework combines a patient’s electronic health record data with clinical guideline representation to obtain personalised recommendations, uses computational argumentation techniques to resolve conflicts among recommendations while respecting preferences of various parties involved, if any, and yields conflict-free recommendations that are inspectable and explainable. The system implementing our framework will allow for continuous learning by taking feedback from the decision makers and integrating it within its pipeline.