.png){kind=icon}
.png){kind=icon}
Return
Analyzing interactions on combining multiple clinical guidelines
.png){kind=icon}
OA
AI
DOI：10.1016/j.artmed.2017.03.012.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Accounting for patients with multiple health conditions is a complex task that requires analysing potential interactions among recommendations meant to address each condition. Although some approaches have been proposed to address this issue, important features still require more investigation, such as (re)usability and scalability. To this end, this paper presents an approach that relies on reusable rules for detecting interactions among recommendations coming from various guidelines. It extends a previously proposed knowledge representation model (TMR) to enhance the detection of interactions and it provides a systematic analysis of relevant interactions in the context of multimorbidity. The approach is evaluated in a case study on rehabilitation of breast cancer patients, developed in collaboration with experts. The results are considered promising to support the experts in this task. (C) 2017 Elsevier B.V. All rights reserved.
Keywords:
Clinical knowledge representation
Combining clinical guidelines
Multimorbidity
Comorbidity
Interactions among guidelines
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.2
Papers:
2.5K
Citations:
7.8K
Organization
View more organizations