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ACKTUS: A Platform for Developing Personalized Support Systems in the Health Domain
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. (Arcum)
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
2015 (Engelska)Ingår i: Proceedings of the 5th International Conference on Digital Health 2015, 2015, s. 135-142Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

This paper presents ACKTUS, a semantic web platform for modeling and managing knowledge integrated in support systems for health care, and for designing the interaction with the end user applications. A key purpose is to allow the domain experts to collaboratively model the knowledge content and tailor interaction to users. Therefore, the development has been done in a process of participatory action research where domain experts have contributed to the design and re-design of ACKTUS while they have been modeling the content and behavior of end-user applications. The ontology that serves as the knowledge structure in the system integrates the user model, modality values, clinical practice guidelines and preferences, in the form of schemes and scheme-nodes (arguments) in an argumentation framework, partly by integrating the argument interchange format. User studies have shown that ACKTUS can be used for the intended purpose by domain professionals not familiar with knowledge engineering tasks. Moreover, the platform functions as a research infrastructure for health researchers in their development and evaluation of new ICT-based interventions targeting improved health.

Ort, förlag, år, upplaga, sidor
2015. s. 135-142
Nyckelord [en]
cooperative design, decision-support systems, e-health, interaction design, knowledge engineering, ontology, personalisation, semantic web, user modelling
Nationell ämneskategori
Datavetenskap (datalogi) Människa-datorinteraktion (interaktionsdesign)
Forskningsämne
datalogi; människa-dator interaktion; medicinsk informatik
Identifikatorer
URN: urn:nbn:se:umu:diva-103669DOI: 10.1145/2750511.2750526OAI: oai:DiVA.org:umu-103669DiVA, id: diva2:814399
Konferens
DH '15 Digital Health 2015 Conference Florence, Italy — May 18 - 20, 2015
Tillgänglig från: 2015-05-26 Skapad: 2015-05-26 Senast uppdaterad: 2018-08-21Bibliografiskt granskad
Ingår i avhandling
1. Developing digital support for learning and diagnostic reasoning in clinical practice
Öppna denna publikation i ny flik eller fönster >>Developing digital support for learning and diagnostic reasoning in clinical practice
2018 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

The two main purposes of clinical decision-support systems (CDSSs) are to provide healthcare professionals decision-making support based on evidence-based medical knowledge, and a continuing medical education. This thesis focuses on both purposes and shows how fundamental theory in the field of artificial intelligence can be developed, adapted and implemented in a CDSS for supporting learning and diagnostic reasoning in clinical practice. The main research problems addressed in this thesis are how to represent and manage uncertain, incomplete, inconsistent and distributed knowledge in automated reasoning and decision-making with the clinicians in the loop, how to facilitate the knowledge engineering and maintenance process, and how to detect and support learning and skill development in CDSS users.

Research contributions include theories, methods, and algorithms based on possibilistic logic and formal argumentation for representing and managing uncertain, incomplete, inconsistent and distributed medical knowledge, and for supporting reasoning and decision-making when using a CDSS. The clinician is provided potentially conflicting arguments and their strength based on different diagnostic criteria and the available patient information in order to make an informed decision. The theoretical results were implemented in the Dementia Diagnosis and Management Support System - Web version (DMSS-W), in a multi-agent hypothesis-driven inquiry dialogue system, and in an inference engine serving as a module of ACKTUS.

CDSS maintenance is challenging since new knowledge about diseases and treatments are continuously developed. Typically, knowledge and software engineers are needed to bridge medical experts and CDSSs, leading to time-consuming system development. ACKTUS (Activity-Centered Knowledge and Interaction Tailored to Users) was, as part of this research, further developed as a generic web-based platform for knowledge management and end-user development of CDSSs. It includes the inference engine and a content management system that the medical expert can use to manage knowledge, design and evaluate CDSSs. A graphical user interface generator synchronizes the interface to the ontology serving as the knowledge base. ACKTUS was used for developing DMSS-W, and facilitated the system development and maintenance.

To offer person-tailored support for the clinician's learning, reasoning and decision-making, the CDSS design was based on theories of how novices and experts reason and make decisions. Pilot case studies involving physicians with different levels of expertise who applied DMSS-W in patient cases were conducted in clinical practice to explore methods for detecting skill levels and whether learning is taking place. The results indicated that the skill levels can be detected using the method. The novice was seen to develop reasoning strategies similar to an expert's, indicating that learning was taking place. In future work, tailored educational support will be developed, and evaluated using the methods.

Ort, förlag, år, upplaga, sidor
Umeå: Umeå University, 2018. s. 49
Serie
Report / UMINF, ISSN 0348-0542 ; 18.09
Nyckelord
Clinical decision-support systems, knowledge representation, possibilistic logic, multi-agent systems, formal argumentation, ontology, automated decision making, inquiry dialogue, end-user development, continuing medical education, dementia
Nationell ämneskategori
Datorsystem
Identifikatorer
urn:nbn:se:umu:diva-150922 (URN)978-91-7601-918-4 (ISBN)
Disputation
2018-09-27, MA121, MIT-huset, Umeå, 13:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2018-08-23 Skapad: 2018-08-20 Senast uppdaterad: 2018-08-21Bibliografiskt granskad

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Lindgren, HelenaYan, Chunli

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Lindgren, HelenaYan, Chunli
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