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Yan, C., Lindgren, H. & Nieves, J. C. (2018). A Dialogue-Based Approach for Dealing with Uncertain and Conflicting Information in Medical Diagnosis. Autonomous Agents and Multi-Agent Systems, 32(6), 861-885
Open this publication in new window or tab >>A Dialogue-Based Approach for Dealing with Uncertain and Conflicting Information in Medical Diagnosis
2018 (English)In: Autonomous Agents and Multi-Agent Systems, ISSN 1387-2532, E-ISSN 1573-7454, Vol. 32, no 6, p. 861-885Article in journal (Refereed) Published
Abstract [en]

In this paper, we propose a multi-agent framework to deal with situations involving uncertain or inconsistent information located in a distributed environment which cannot be combined into a single knowledge base. To this end, we introduce an inquiry dialogue approach based on a combination of possibilistic logic and a formal argumentation-based theory, where possibilistic logic is used to capture uncertain information, and the argumentation-based approach is used to deal with inconsistent knowledge in a distributed environment. We also modify the framework of earlier work, so that the system is not only easier to implement but also more suitable for educational purposes. The suggested approach is implemented in a clinical decision-support system in the domain of dementia diagnosis. The approach allows the physician to suggest a hypothetical diagnosis in a patient case, which is verified through the dialogue if sufficient patient information is present. If not, the user is informed about the missing information and potential inconsistencies in the information as a way to provide support for continuing medical education. The approach is presented, discussed, and applied to one scenario. The results contribute to the theory and application of inquiry dialogues in situations where the data are uncertain and inconsistent.

Place, publisher, year, edition, pages
Springer, 2018
Keywords
Multi-agent system, Inquiry dialogues, Possibilistic logic, Argumentation framework
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:umu:diva-150966 (URN)10.1007/s10458-018-9396-x (DOI)000446664700004 ()
Available from: 2018-08-21 Created: 2018-08-21 Last updated: 2018-11-02Bibliographically approved
Yan, C. & Lindgren, H. (2018). A Generic Approach for Data Management and End-User Development of Clinical Decision Support Systems. Umeå universitet
Open this publication in new window or tab >>A Generic Approach for Data Management and End-User Development of Clinical Decision Support Systems
2018 (English)Report (Other academic)
Abstract [en]

The main purposes of clinical decision-support systems (CDSS) are disseminating evidence-based medical knowledge (EBM), supporting a continued medical education, and improving clinical decision making and care. These purposes are traditionally achieved by using solutions that are relatively transparent and explainable to the end user. However, the development and maintenance of such solutions is resource demanding. Currently, there are four challenges existing in CDSSs when adapting to new circumstances. That is, when facing new knowledge, new diseases, different organizations and users with different skills, usually one needs to update the existing CDSS or develop a new CDSS, which requires lots of time and efforts. Hence, this paper aims for reusing an existing CDSS code by virtue of inputs from authorized medical domain expert users, and with minimal requirement of knowledge and software engineers. To facilitate knowledge elicitation and end-user development, an ACKTUS-based architecture for CDSS development and management is presented that contains: I) A knowledge base and a content management system built on Semantic Web technology to achieve modularity, reusability, customisation, and the possibility to allow medical experts to model the medical knowledge and to structure the information that builds up the design of the user interface; II) A user interface and an graphical user interface generator that automatically generates the user interface whenever the user logs in, so that the interface is synchronised with updates of the knowledge base; III) An inference engine that utilizes patient-specific data and applies various rules in the knowledge base to conduct the reasoning and decision making. These modules can be reused when adapting to new situations. A CDSS for dementia diagnosis is developed and used as an example in the presentation of the generic architecture. A pilot study of the CDSS is presented involving four medical professionals with different levels of expertise. The results show how the generic approach allows for easy knowledge representation and management of EBM, supports a continued medical education and may improve clinical decision making and care provision.

Place, publisher, year, edition, pages
Umeå universitet, 2018. p. 25
Series
Report / UMINF, ISSN 0348-0542 ; 18.08
Keywords
CDSS, Data Management, Knowledge Acquisition, Ontology, Semantic Web
National Category
Information Systems Human Computer Interaction
Identifiers
urn:nbn:se:umu:diva-150968 (URN)
Available from: 2018-08-21 Created: 2018-08-21 Last updated: 2018-08-21Bibliographically approved
Lindgren, H., Lu, M.-H., Hong, Y. & Yan, C. (2018). Applying the zone of proximal development when evaluating clinical decision support systems: a case study. In: Adrien Ugon, Daniel Karlsson, Gunnar O. Klein, Anne Moen (Ed.), Building continents of knowledge in oceans of data: The future of co-created eHealth (pp. 131-135). IOS Press, 247
Open this publication in new window or tab >>Applying the zone of proximal development when evaluating clinical decision support systems: a case study
2018 (English)In: Building continents of knowledge in oceans of data: The future of co-created eHealth / [ed] Adrien Ugon, Daniel Karlsson, Gunnar O. Klein, Anne Moen, IOS Press, 2018, Vol. 247, p. 131-135Chapter in book (Refereed)
Abstract [en]

The goal to facilitate a continuing medical education can be incorporated in the design of a clinical decision-support system. Developing a method for evaluating knowledge and skill development as part of evaluating the system is the aim for the research presented in this paper. The activity supported by the system was analyzed using Activity theory and structured into a protocol. Four clinicians were studied using the system for the first time, and their activity were assessed using the concept of Zone of Proximal Development. Initial results show how the system was used for clinician with different level of skills, and provide implications for further development of the methodology and the system.

Place, publisher, year, edition, pages
IOS Press, 2018
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365 ; 247
Keywords
Activity theory, Clinical decision-support system, Continuing medical education, Dementia, Evaluation, Zone of proximal development
National Category
Human Computer Interaction
Research subject
människa-datorinteraktion; medicinsk informatik
Identifiers
urn:nbn:se:umu:diva-146892 (URN)10.3233/978-1-61499-852-5-131 (DOI)29677937 (PubMedID)978-1-61499-851-8 (ISBN)978-1-61499-852-5 (ISBN)
Available from: 2018-04-23 Created: 2018-04-23 Last updated: 2018-06-09Bibliographically approved
Yan, C. (2018). Developing digital support for learning and diagnostic reasoning in clinical practice. (Doctoral dissertation). Umeå: Umeå University
Open this publication in new window or tab >>Developing digital support for learning and diagnostic reasoning in clinical practice
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2018. p. 49
Series
Report / UMINF, ISSN 0348-0542 ; 18.09
Keywords
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
National Category
Computer Systems
Identifiers
urn:nbn:se:umu:diva-150922 (URN)978-91-7601-918-4 (ISBN)
Public defence
2018-09-27, MA121, MIT-huset, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2018-08-23 Created: 2018-08-20 Last updated: 2018-08-21Bibliographically approved
Zhang, G., Zhao, M., Yan, C., Sun, B., Wu, Z., Chang, H., . . . Liu, H. (2018). Thermal Analysis of AlGaN/GaN High-Electron-Mobility Transistors with Graphene. Journal of Nanoscience and Nanotechnology, 18(11), 7578-7583
Open this publication in new window or tab >>Thermal Analysis of AlGaN/GaN High-Electron-Mobility Transistors with Graphene
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2018 (English)In: Journal of Nanoscience and Nanotechnology, ISSN 1533-4880, E-ISSN 1533-4899, Vol. 18, no 11, p. 7578-7583Article in journal (Refereed) Published
Abstract [en]

A thermal analysis of AlGaN/GaN high electron mobility transistors (HEMTs) with Graphene is investigated using Silvaco and Finite Element Method. Two thermal management solutions are adopted; first of all, graphene is used as dissipation material between SiC substrate and GaN buffer layer to reduce thermal boundary resistance of the device. At the same time, graphene is also used as a thermal spread material on the top of the source contacts to reduce thermal resistance of the device. The thermal analysis results show that the temperature rise of device adopting graphene decreases by 46.5% in transistors operating at 13.86 W/mm. Meanwhile, the thermal resistance of GaN HEMTs with graphene is 6.8 K/W, which is much lower than the device without graphene, which is 18.5 K/W. The thermal management solutions are useful for integration of large-scale graphene into practical devices for effective heat spreading in AlGaN/GaN HEMT.

Place, publisher, year, edition, pages
American Scientific Publishers, 2018
Keywords
AlGaN/GaN, High-Electron-Mobility Transistors (HEMTs), Graphene, Thermal Management
National Category
Condensed Matter Physics
Identifiers
urn:nbn:se:umu:diva-152372 (URN)10.1166/jnn.2018.16080 (DOI)000443946600045 ()
Available from: 2018-10-05 Created: 2018-10-05 Last updated: 2018-10-05Bibliographically approved
Yan, C. & Lindgren, H. (2017). Diagnostic Reasoning Guided by a Decision-Support System: a Case Study. In: Proceedings of the European Conference on Cognitive Ergonomics 2017: Transforming the everyday. Paper presented at ECCE 2017, European Conference on Cognitive Ergonomics, Transforming the everyday, 20-22 September 2017, Umeå University, Sweden (pp. 25-30). New York, NY, USA: ACM Digital Library
Open this publication in new window or tab >>Diagnostic Reasoning Guided by a Decision-Support System: a Case Study
2017 (English)In: Proceedings of the European Conference on Cognitive Ergonomics 2017: Transforming the everyday, New York, NY, USA: ACM Digital Library, 2017, p. 25-30Conference paper, Published paper (Refereed)
Abstract [en]

A clinical decision-support system for dementia investigation was used in clinical practice. User information was collected based on interactions with the application. The aim of this study is to identify features in logged data that can be used for detecting learning and reasoning patterns in the user. A case of a physician who is novice to both the application and the dementia domain was studied and compared to the case of an expert physician using the system. Diferences between them were found, and a clear pattern that indicates that learning takes place, both how to use the system and about dementia, was observed in the novice user. Further studies need to be conducted, focusing on whether patterns become stable over time, and with complementary methods that can detect reasons for observed behaviors. Software for automatic detection will be developed based on the results of this study.

Place, publisher, year, edition, pages
New York, NY, USA: ACM Digital Library, 2017
Keywords
Diagnostic reasoning, Clinical decision support systems, Dementia, Continued medical education, Cognition
National Category
Computer Sciences Human Computer Interaction
Research subject
Computer and Information Science; människa-datorinteraktion; medicinsk informatik
Identifiers
urn:nbn:se:umu:diva-141027 (URN)10.1145/3121283.3121307 (DOI)978-1-4503-5256-7 (ISBN)
Conference
ECCE 2017, European Conference on Cognitive Ergonomics, Transforming the everyday, 20-22 September 2017, Umeå University, Sweden
Available from: 2017-10-22 Created: 2017-10-22 Last updated: 2018-08-21Bibliographically approved
Baskar, J., Yan, C. & Lindgren, H. (2017). Instrument-Oriented Approach to Detecting and Representing Human Activity for Supporting Executive Functions and Learning. In: Proceedings of the European Conference on Cognitive Ergonomics 2017: . Paper presented at European Conference on Cognitive Ergonomics (ECCE) 2017, Umeå, Sweden, September 9-22, 2017 (pp. 105-112). New York, NY, USA: ACM Digital Library
Open this publication in new window or tab >>Instrument-Oriented Approach to Detecting and Representing Human Activity for Supporting Executive Functions and Learning
2017 (English)In: Proceedings of the European Conference on Cognitive Ergonomics 2017, New York, NY, USA: ACM Digital Library, 2017, p. 105-112Conference paper, Published paper (Refereed)
Abstract [en]

The goal of this study is to develop a computer-interpretable model for activity detection and representation, based on existing informal models of how humans perform activity. Appropriate detection of purposeful human activity is an essential functionality of active assistive technology aiming at providing tailored support to individuals for improving activity performance and completion. The main contribution is the design of a model for detection and representation of human activities based on three categories of instruments, which is implemented as two generic and supplementary terminology models: an event ontology and a core ontology. The core ontology is extended for each new knowledge domain into a domain ontology. The model builds the base for personalization of services generated by the cooperative reasoning performed by a human collaborating with an intelligent and social software agent. Ongoing and future work includes user studies in the different application domains.

Place, publisher, year, edition, pages
New York, NY, USA: ACM Digital Library, 2017
Series
Academic dissertations at the department of Educational Measurement, ISSN 1652-9650
Keywords
Activity recognition, Activity theory, Assistive technology, Decision-support systems, Human-agent interaction, Knowledge representation, Ontology, User modelling
National Category
Computer Sciences Human Computer Interaction
Research subject
computer and systems sciences; human-computer interaction
Identifiers
urn:nbn:se:umu:diva-141026 (URN)10.1145/3121283.3121305 (DOI)978-1-4503-5256-7 (ISBN)
Conference
European Conference on Cognitive Ergonomics (ECCE) 2017, Umeå, Sweden, September 9-22, 2017
Available from: 2017-10-22 Created: 2017-10-22 Last updated: 2019-06-26Bibliographically approved
Lindgren, H., Baskar, J., Guerrero, E., Nieves, J. C., Nilsson, I. & Yan, C. (2016). Computer-Supported Assessment for Tailoring Assistive Technology. In: DH'16: PROCEEDINGS OF THE 2016 DIGITAL HEALTH CONFERENCE: . Paper presented at 6th International Conference on Digital Health (DH), APR 11-13, 2016,Montreal, CANADA (pp. 1-10). New York: Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Computer-Supported Assessment for Tailoring Assistive Technology
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2016 (English)In: DH'16: PROCEEDINGS OF THE 2016 DIGITAL HEALTH CONFERENCE, New York: Association for Computing Machinery (ACM), 2016, p. 1-10Conference paper, Published paper (Refereed)
Abstract [en]

The main purpose of assistive technology is to support an individual's daily activities, in order to increase ability, autonomy, relatedness and quality of life. The aim for the work presented in this article is to develop automated methods to tailor the behavior of the assistive technology for the purpose to provide just-in-time, adaptive interventions targeting multiple domains. This requires methods for representing and updating the user model, including goals, preferences, abilities, activity and its situation. We focus the assessment and intervention tasks typically performed by therapists and provide knowledge-based technology for supporting the process. A formative evaluation study was conducted as a part of a participatory action research process, involving two rehabilitation experts, two young individuals and one senior individual as end-user participants, in addition to knowledge engineers. The main contribution of this work is a theory-based method for assessing the individual's goals, preferences, abilities and motives, which is used for building a holistic user model. The user model is continuously updated and functions as the base for tailoring the system's assistive behavior during intervention and follow-up.

Place, publisher, year, edition, pages
New York: Association for Computing Machinery (ACM), 2016
Keywords
Knowledge-based systems, User modeling, Personalization, Assistive technology, End-user development, Ambient assisted living, Multi-agent systems, Mental health, Behavior change systems, Participatory action research
National Category
Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:umu:diva-128874 (URN)10.1145/2896338.2896352 (DOI)000390308300001 ()978-1-4503-4224-7 (ISBN)
Conference
6th International Conference on Digital Health (DH), APR 11-13, 2016,Montreal, CANADA
Available from: 2016-12-17 Created: 2016-12-17 Last updated: 2018-06-09Bibliographically approved
Lindgren, H. & Yan, C. (2015). ACKTUS: A Platform for Developing Personalized Support Systems in the Health Domain. In: Proceedings of the 5th International Conference on Digital Health 2015: . Paper presented at DH '15 Digital Health 2015 Conference Florence, Italy — May 18 - 20, 2015 (pp. 135-142).
Open this publication in new window or tab >>ACKTUS: A Platform for Developing Personalized Support Systems in the Health Domain
2015 (English)In: Proceedings of the 5th International Conference on Digital Health 2015, 2015, p. 135-142Conference paper, Published paper (Refereed)
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.

Keywords
cooperative design, decision-support systems, e-health, interaction design, knowledge engineering, ontology, personalisation, semantic web, user modelling
National Category
Computer Sciences Human Computer Interaction
Research subject
Computer Science; människa-dator interaktion; medicinsk informatik
Identifiers
urn:nbn:se:umu:diva-103669 (URN)10.1145/2750511.2750526 (DOI)
External cooperation:
Conference
DH '15 Digital Health 2015 Conference Florence, Italy — May 18 - 20, 2015
Available from: 2015-05-26 Created: 2015-05-26 Last updated: 2018-08-21Bibliographically approved
Lindgren, H. & Yan, C. (2015). Detecting Learning and Reasoning Patterns in a CDSS for Dementia Investigation. Studies in Health Technology and Informatics, 210, 739-742
Open this publication in new window or tab >>Detecting Learning and Reasoning Patterns in a CDSS for Dementia Investigation
2015 (English)In: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 210, p. 739-742Article in journal (Refereed) Published
Abstract [en]

Reasoning conducted in clinical practice is manifested through different and often combined reasoning and learning strategies, adjusted to the characteristics of the available information, the medical professional's experience and skills, and the available tools, such as clinical practice guidelines. This research outlines a design model for supporting the commonly used strategies. This design model was implemented into a clinical decision-support system (CDSS), in addition to a method for detecting reasoning strategies applied when using the CDSS. This method was applied in a case study, with preliminary results presented in this paper and will be further implemented in future studies.

Place, publisher, year, edition, pages
IOS Press, 2015
National Category
Computer Sciences
Research subject
medicinsk informatik; människa-dator interaktion; Computer Science
Identifiers
urn:nbn:se:umu:diva-103668 (URN)25991251 (PubMedID)
External cooperation:
Available from: 2015-05-26 Created: 2015-05-26 Last updated: 2018-08-21Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-5984-5604

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