Assumption-based argumentation with preferences and goals for patient-centric reasoning with interacting clinical guidelines
File(s)aac_2021_12-2_aac-12-2-aac200523_aac-12-aac200523.pdf (1.09 MB)
Published version
Author(s)
Cyras, Kristijonas
Oliveira, Tiago
Karamlou, Mohammad
Toni, Francesca
Type
Journal Article
Abstract
A paramount, yet unresolved issue in personalised medicine is that of automated reasoning with clinical guidelines in multimorbidity settings. This entails enabling machines to use computerised generic clinical guideline recommendations and patient-specific information to yield patient-tailored recommendations where interactions arising due to multimorbidities are resolved. This problem is further complicated by patient management desiderata, in particular the need to account for patient-centric goals as well as preferences of various parties involved. We propose to solve this problem of automated reasoning with interacting guideline recommendations in the context of a given patient by means of computational argumentation. In particular, we advance a structured argumentation formalism ABA+G (short for Assumption-Based Argumentation with Preferences (ABA+) and Goals) for integrating and reasoning with information about recommendations, interactions, patient’s state, preferences and prioritised goals. ABA+G combines assumption-based reasoning with preferences and goal-driven selection among reasoning outcomes. Specifically, we assume defeasible applicability of guideline recommendations with the general goal of patient well-being, resolve interactions (conflicts and otherwise undesirable situations) among recommendations based on the state and preferences of the patient, and employ patient-centered goals to suggest interaction-resolving, goal-importance maximising and preference-adhering recommendations. We use a well-established Transition-based Medical Recommendation model for representing guideline recommendations and identifying interactions thereof, and map the components in question, together with the given patient’s state, prioritised goals, and preferences over actions, to ABA+G for automated reasoning. In this, we follow principles of patient management and establish corresponding theoretical properties as well as illustrate our approach in realistic personalised clinical reasoning scenaria.
Date Issued
2021-06-09
Date Acceptance
2020-10-27
Citation
Argument and Computation, 2021, 12 (2), pp.149-189
ISSN
1946-2166
Publisher
Taylor and Francis
Start Page
149
End Page
189
Journal / Book Title
Argument and Computation
Volume
12
Issue
2
Copyright Statement
© 2021 – The authors. Published by IOS Press. This is an Open Access article distributed under the terms of theCreative Commons Attribution-NonCommercial License (CC BY-NC 4.0).
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/P029558/1
Subjects
0801 Artificial Intelligence and Image Processing
1702 Cognitive Sciences
2203 Philosophy
Publication Status
Published