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Michalowski M.,Adventium Labs | Wilk S.,Poznan University of Technology | Tan X.,University of Ottawa | Michalowski W.,University of Ottawa
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium | Year: 2014

Clinical practice guidelines (CPGs) implement evidence-based medicine designed to help generate a therapy for a patient suffering from a single disease. When applied to a comorbid patient, the concurrent combination of treatment steps from multiple CPGs is susceptible to adverse interactions in the resulting combined therapy (i.e., a therapy established according to all considered CPGs). This inability to concurrently apply CPGs has been shown to be one of the key shortcomings of CPG uptake in a clinical setting1. Several research efforts are underway to address this issue such as the K4CARE2 and GuideLine INteraction Detection Assistant (GLINDA)3 projects and our previous research on applying constraint logic programming to developing a consistent combined therapy for a comorbid patient4. However, there is no generalized framework for mitigation that effectively captures general characteristics of the problem while handling nuances such as time and ordering requirements imposed by specific CPGs. In this paper we propose a first-order logic-based (FOL) approach for developing a generalized framework of mitigation. This approach uses a meta-algorithm and entailment properties to mitigate (i.e., identify and address) adverse interactions introduced by concurrently applied CPGs. We use an illustrative case study of a patient suffering from type 2 diabetes being treated for an onset of severe rheumatoid arthritis to show the expressiveness and robustness of our proposed FOL-based approach, and we discuss its appropriateness as the basis for the generalized theory.

Boddy M.,Adventium Labs
ICAPS 2012 - 22nd International Conference on Automated Planning and Scheduling; COPLAS 2012 - Proceedings of the Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems | Year: 2012

We are concerned with the problem of optimizing network resource allocations to mission tasks. The model includes unreliable network assets, multiple mission tasks and phases, and the possibility of over-provisioning one or more tasks as a means of increasing the likelihood of task success. In this paper, we describe an implemented approach to optimizing network resources so as to optimize the expected utility of the mission. This differs significantly from previous work on cloud and network management, where the objective was to optimize some operational measure of the network itself, rather than the effect of network failures on a specific task. The work described here is preliminary: we describe the problem and the approach, define an architecture, and present the current state of the implementation. Copyright © 2012, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Hing M.M.,University of Ottawa | Michalowski M.,Adventium Labs | Wilk S.,Poznan University of Technology | Michalowski W.,University of Ottawa | Farion K.,Children Hospital of Eastern Ontario
2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010 | Year: 2010

This paper describes a methodological approach to identifying inconsistencies when reconciling multiple clinical practice guidelines. The need to address these inconsistencies arises when a patient with co-morbidity has to be managed according to different treatment regimens. Starting with a well-known flowchart representation we discuss how to create a formal guideline model that allows for easy manipulations of its components. For this model we present how to identify conflicting actions that are manifested by treatment-treatment and treatment-disease interactions, and how to reconcile these conflicting actions. ©2010 IEEE.

Wilk S.,Poznan University of Technology | Michalowski W.,University of Ottawa | Michalowski M.,Adventium Labs | Farion K.,Childrens Hospital of Eastern Ontario | And 2 more authors.
Journal of Biomedical Informatics | Year: 2013

We propose a new method to mitigate (identify and address) adverse interactions (drug-drug or drug-disease) that occur when a patient with comorbid diseases is managed according to two concurrently applied clinical practice guidelines (CPGs). A lack of methods to facilitate the concurrent application of CPGs severely limits their use in clinical practice and the development of such methods is one of the grand challenges for clinical decision support. The proposed method responds to this challenge.We introduce and formally define logical models of CPGs and other related concepts, and develop the mitigation algorithm that operates on these concepts. In the algorithm we combine domain knowledge encoded as interaction and revision operators using the constraint logic programming (CLP) paradigm. The operators characterize adverse interactions and describe revisions to logical models required to address these interactions, while CLP allows us to efficiently solve the logical models - a solution represents a feasible therapy that may be safely applied to a patient.The mitigation algorithm accepts two CPGs and available (likely incomplete) patient information. It reports whether mitigation has been successful or not, and on success it gives a feasible therapy and points at identified interactions (if any) together with the revisions that address them. Thus, we consider the mitigation algorithm as an alerting tool to support a physician in the concurrent application of CPGs that can be implemented as a component of a clinical decision support system. We illustrate our method in the context of two clinical scenarios involving a patient with duodenal ulcer who experiences an episode of transient ischemic attack. © 2013 Elsevier Inc.

Wilk S.,Poznan University of Technology | Michalowski M.,Adventium Labs | Tan X.,University of Ottawa | Michalowski W.,University of Ottawa
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

Clinical practice guidelines (CPGs) were originally designed to help with evidence-based management of a single disease and such single disease focus has impacted research on CPG computerization. This computerization is mostly concerned with supporting different representation formats and identifying potential inconsistencies in the definitions of CPGs. However, one of the biggest challenges facing physicians is the application of multiple CPGs to comorbid patients. While various research initiatives propose ways of mitigating adverse interactions in concurrently applied CPGs, there are no attempts to develop a generalized framework for mitigation that captures generic characteristics of the problem, while handling nuances such as precedence relationships. In this paper we present our research towards developing a mitigation framework that relies on a first-order logic-based representation and related theorem proving and model finding techniques. The application of the proposed framework is illustrated with a simple clinical example. © Springer International Publishing Switzerland 2014.

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