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Methods and tools for the development of computer-interpretable guidelines

Asbru
  Asbru is a task-specific and intention-based plan representation language to embody clinical guidelines and protocols as time-oriented skeletal plans. Skeletal plans provide a powerful way to reuse existing domain-specific procedural knowledge, while leaving room for execution-time flexibility to achieve particular goals.
The Asbru plan and guideline language and associated technologies have been developed by the Asgaard/Asbru project. Asgaard was the home and citadel of the gods in Norse mythology, corresponding to Mount Olympus in Greek mythology. It was located in the heavens and was accessible only over the rainbow bridge, called Asbru (or Bifrost).
keywords Knowledge representation, knowledge acquisition, computer-interpretable guidelines, task-specific, intention-based, skeletal plans, representing, reasoning with, visualizing time-oriented patient data
developed by The Asgaard project led by the Vienna University of Technology and Stanford Medical Informatics.
introduced 1998
status Under evaluation / in use / under continued development (including development and support tools).
support  
in use Prototype applications in diabetes, jaundice and breast cancer.
tools Associated downloadable prototype software tools include:

 bullet  AsbruView - Graphical user interface to Asbru to support visualization and understanding of Asbru guidelines [OC]  bullet  CareVis - Integrated Visualization of Computerized Protocols and Temporal Patient Data [OC]  bullet  DELT/A - Document Exploration and Linking Tool [OC]

description

Asbru enables the designer to represent both the prescribed actions of a skeletal plan and the knowledge roles required by the various problem-solving methods performing the intertwined supporting subtasks. 

Asbru enables the intentions and goals of a guideline and the temporal dimensions and uncertainties to be defined as an intrinsic part of that guideline. This supports the appropriate application of a guideline in practice and the quality assessment of its application.

Main features:

  • Prescribed actions and states can be continuous;
  • Intentions, conditions, and world states are temporal pattern;
  • Uncertainty in both temporal scopes and parameters can be flexibly expressed by bounding intervals;
  • Plans might be executed in sequence, all plans or some plans in parallel, all plans or some plans in a particular order, or periodically;
  • Particular conditions are defined to monitor the plans’ execution;
  • Explicit intentions and preferences can be stated for each plan separately. (Intentions are temporal-pattern constraints, e.g., a process intention to administer regular insulin twice a day; an outcome intention to maintain fasting blood glucose within a certain range over at least 5 days a week, that are allocated individual weights signifying their relative importance. Such knowledge is necessary to determine, for instance, whether a care provider is still following most of the guideline, or, at least, its spirit. Such a provider might be applying the guideline in modified fashion, as is, in fact, the case in 50% of inspected guideline applications.)

current work 1: Plan Execution and Analysis - Data Abstraction

Temporal data abstraction bridges the gap between low-level data delivered by, e.g., monitoring devices in an intensive care unit and high-level concepts used, e.g., in treatment plans. Two persisting problems are varying data quality and abstractions which meet the intuitions of physicians. To cope with these problems, we developed an algorithm called the Spread and abstractions of repeated patterns which promise to match closely the human perception of graphs in addition to extracting features not directly visible.

A related project (Using Pulsoximetry and Time-Oriented Data Abstraction Methods to Optimize Oxygen Supply for Neonates) is currently evaluating a subset of these methods in a clinical setting, namely the supply of oxigen to preterm neonates.

current work 2: Guideline and Protocol Authoring
Three activities in this area are being undertaken by three separate groups in Amsterdam, Beer Sheva, Israel and Vienna.

 The AI Department, Vrije Universiteit Amsterdam (Frank van Harmelen's group) is developing an intermediate representation to visualize the upper part of the Asbru language hierarchy as boxes in HTML.

  Ben Gurion University of the Negev, Beer Sheva, Israel (Yuval Shahar's group) is developing DeGeL: Digital Guidelines Library.

DeGeL is a hybrid, multifaceted representation language and computerized, Web-based set of tools for storage, authoring, retrieval and enactment of Asbru-based clinical guidelines.

The DeGeL method is designed to support the translation of text-based guidelines firstly to structured text (in XML, segmented and labelled by Asbru semantic tags), then into a fully formal, machine-readable, and machine-executable (Asbru) representation. It is envisaged that the first of these phases, marking up existing text and adding appropriate semantic labels, will be carried out by physicians, and that knowledge engineers will convert the resulting highly structured XML-based text into Asbru.

Each guideline might therefore exist as free text, XML, or Asbru, or even combinations of the three (for example, the guideline's entry conditions might well be the first priority for conversion into Asbru, thus supporting automated eligibility determination). At the same time, by developing computational tools that can handle each representation format, the automated services that the guideline's representation can support are gradually being enhanced (e.g. from simple full-text search, to context-sensitive retrieval and visualization, and finally, to automated application and quality assessment), while providing demonstrable value (such as enhanced precision of search and retrieval) at each phase.

  The Vienna University of Technology, Institute of Software Technology and Interactive Systems (Silvia Miksch's group) is developing DELT/A to provide a relatively easy way to translate free text into Asbru. It achieves this by displaying both the original text and the translation, and showing the user which parts of the Asbru code correspond to which elements of the original text. This not only makes it easier to author plans, but also to understand the resulting Asbru constructs in terms of the original guideline.

current work 3: Verification and Validation of Protocols
The Protocure II project, funded by the EU 5FP IST program, is investigating and validating formal methods to improve medical protocols written in Asbru.
current work 4: Information Visualization
The Vienna University of Technology, Institute of Software Technology and Interactive Systems is developing AsbruView - Graphical user interface to Asbru to support visualization and understanding of Asbru guidelines, and CareVis - Integrated Visualization of Computerized Protocols and Temporal Patient Data, further details on which can be found on this site (see links below).
references: introductory papers on Asbru
Shahar, Y., Miksch, S., and Johnson, P. The Asgaard project: A task-specific framework for the application and critiquing of time-oriented clinical guidelines. Artificial Intelligence in Medicine (14): 29-51, 1998.

[SMI]     []

" Clinical guidelines can be viewed as generic skeletal-plan schemata that represent clinical procedural knowledge and that are instantiated and refined dynamically by care providers over significant time periods. In the Asgaard project, we are investigating a set of tasks that support the application of clinical guidelines by a care provider other than the guideline's designer. We are focusing on application of the guideline, recognition of care providers' intentions from their actions, and critique of care providers' actions given the guideline and the patient's medical record. We are developing methods that perform these tasks in multiple clinical domains, given an instance of a properly represented clinical guideline and an electronic medical patient record. In this paper, we point out the precise domain-specific knowledge required by each method, such as the explicit intentions of the guideline designer (represented as temporal patterns to be achieved or avoided). We present a machine-readable language, called Asbru, to represent and to annotate guidelines based on the task-specific ontology. We also introduce an automated tool for acquisition of clinical guidelines based on the same ontology, developed using the PROTEGE-II framework. "
Advani A, Lo K, Shahar Y. Intention-based critiquing of guideline-oriented medical care. Proc AMIA Symp 1998;:483-7.

[PubMed]    []

" We present a methodology and tool for providing retrospective review and critiquing of guideline-based medical care given to patients. We show how our guideline representation language, Asbru, which supports the use of physicians intentions in addition to physician's actions, allows us to compare the care given to a patient at the level of the intention to treat in addition to the more detailed plan carried out. We have developed an algorithm based on this representation for retrospective quality assessment of guideline-based care. Our method takes the physician's and institution's preferences and policies into account in explaining or justifying physician deviations from the recommendations of a guideline. "

Miksch S. Plan Management in the Medical Domain. AI Communications, 12(4), pp. 209-235, 1999.

[]    [Paper]

"The need to improve the quality of health care has led to a strong demand for clinical protocols and computer systems supporting both their creation and execution. Current approaches in the planning community concentrate on algorithmic improvements, but mostly fail in medical applications. Planning approaches are based on assumptions like deterministic behavior, which do not hold in medical domains. Additionally, they do not cover the problem area of acquisition and verifying complex domain knowledge. In the field of medicine there is a strong movement towards clinical protocols – resembling plans in AI – but computer support during execution of these plans (e.g., controlling, selection of alternatives) is still basic. We need to build complex plans, but also to reason about them in different ways in order to modify plans, to consider the effects of different plans over time, and to monitor execution. We call this range of reasoning tasks plan management. We describe the requirements for these intertwined tasks of plan management so as to respond to the practical demands, to compare approaches in planning and medical informatics to these requirements, and finally, to discuss how our Asgaard project can meet them."

references: modelling, authoring, verification and maintenance with Asbru
Seyfang, A.; Miksch, S.; Marcos, M.: Combining Diagnosis and Treatment using Asbru, International Journal of Medical Informatics, pp. 49-57, 68 (1-3), December 2002.

[PubMed]

[Vienna University Of Technology< ]
[IJMI - Paper]

" Traditionally, diagnosis and treatment have been seen as two distinct tasks. Consequently, most approaches to computer supported health care focus on one of the two-mostly on diagnosis or rather on the interpretation of measurements which is much better understood and formalised. However, in practice diagnosis and treatment overlap and influence each other in many ways. Combinations range from repeatedly going through the diagnosis-treatment loop over a period of time to permanent monitoring of the patients' health condition as it is done in intensive care units. In this article we describe how to model these combinations using the clinical protocol-representation language Asbru. It implements treatment steps in a hierarchy of skeletal, time-oriented plans. Diagnosis can either be described in a declarative way in the conditions, under which treatment steps are taken or it can be modelled explicitly as plans of their own right. We demonstrate our approach using examples taken from the American Association of Paediatricians' guideline for the treatment of hyperbilirubinemia in the new-born. "

Votruba P, Miksch S, Seyfang A, Kosara R. Tracing the formalization steps of textual guidelines. Stud Health Technol Inform. 2004;101:172-6.

[PubMed]   [Vienna University of Technology]

" This paper presents a new guideline authoring tool, called Guideline Markup Tool (GMT). It proposes two useful features, which are missing in existing tools. First, it facilitates the translation of a free-text guideline into a formal representation, providing special XML macros. Second, it can be used to create links between the original guideline and its formal representation. Therefore, the GMT eases the implementation of clinical guidelines in a formal representation, which can be used in monitoring and therapy planning systems. "

Votruba P, Miksch S, Kosara R. Facilitating knowledge maintenance of clinical guidelines and protocols. Medinfo. 2004;11(Pt 1):57-61.

[PubMed]   []

" Clinical protocols and guidelines are widely used in the medi-cal domain to improve disease management techniques. Different software systems are in development to support the de-sign and the execution of such guidelines. The bottleneck in the guideline software developing process is the transformation of the text-based clinical guidelines into a formal representation, which can be used by the execution software. This paper introduces a method and a tool that was designed to provide a solution for that bottleneck. The so-called Guideline Markup Tool (GMT) facilitates the translation of guidelines into a formal representation written in XML. This tool enables the protocol designer to create links between the original guideline and its formal representation and ease the editing of guidelines applying design patterns in the form of macros. The usefulness of our approach is illustrated using GMT to edit Asbru protocols. We performed a usability study with eight participants to examine the usefulness of the GMT and of the Asbru macros, which showed that the proposed approach is very appropriate to author and maintain clinical guidelines. "

Kosara, R.; Miksch, S.; Seyfang, A. and Votruba P.: Tools for Acquiring Clinical Guidelines in Asbru, in Proceedings of the Proceedings of Sixth World Conference on Integrated Design and Process Technology (IDPT'02).

[]    [Paper]

" In order for clinical guidelines to be verified, they must first be acquired or at least translated into a format that can be treated formally. Most guidelines today either exist as plain text, tables, or flow-charts. We present two tools that support this translation: The Guideline Markup Tool (GMT) and the Pontifex Intelligent XML Editor Extension (PIXEE). The GMT provides a relatively easy way to translate free text into Asbru. It does this by displaying both the original text and the translation, and showing the user which parts of the Asbru code correspond to which elements of the original text. This not only makes it easier to author plans, but also to understand the resulting Asbru constructs in terms of the original guideline. PIXEE is a more general XML editor that has some special features due to a richer representation of the language than pure XML. It provides means to aggregate information dynamically and also to more effectively work with language constructs. Both these tools make the translation into a formal language easier and therefore enable us to formally verify guidelines, thus reducing errors and ambiguities in them. "

Seyfang A, Miksch S, Marcos M. Combining diagnosis and treatment using Asbru. Medinfo. 2001;10(Pt 1):533-7.

[PubMed]    [Vienna - paper]

"Traditionally, diagnosis and treatment have been seen as two distinct tasks. Consequently, most approaches to computer supported health care focus on one of the two - mostly on diagnosis or rather on the interpretation of measurements which is much better understood and formalized. However, in practice diagnosis and treatment overlap and influence each other in many ways. Combinations range from repeatedly going through the diagnosis-treatment loop over a period of time to permanent monitoring of the patients' health condition as it is done in intensive care units. In this paper we describe how to model these combinations using the clinical protocol-representation language Asbru. It implements treatment steps in a hierarchy of skeletal, time-oriented plans. Diagnosis can either be described in a declarative way in the conditions, under which treatment steps are taken or it can be modelled explicitly as plans of their own right. We demonstrate our approach using examples taken from the American Association of Paediatricians' guideline for the treatment of hyperbilirubinemia in the new-born."
Marcos, M.; Berger, G.; van Harmelen, F.; ten Teije, A.; Roomans, H.; Miksch, S.: Using Critiquing for Improving Medical Protocols: Harder than it Seems, in Quaglini, S.; Barahona, P.; Andreassen, S. (eds.): Proceedings of European Conference on Artificial Intelligence in Medicine (AIME 2001), Springer, Berlin, pp. 431-441, 2001.

[Abstract]    [Paper]


" Medical protocols are widely recognised to provide clinicians with high-quality and up-to-date recommendations. A critical condition for this is of course that the protocols themselves are of high quality. In this paper we investi-gate the use of critiquing for improving the quality of medical protocols. We constructed a detailed formal model of the jaundice protocol of the American Associ-ation of Pediatrics in the Asbru representation language. We recorded the actions performed by a pediatrician while solving a set of test cases. We then compared these expert actions with the steps recommended by the formalised protocol, and analysed the differences that we observed. Even our relatively small test set of 7 cases revealed many mismatches between the actions performed by the expert and the protocol recommendations, which suggest improvements of the protocol. A major problem in our case study was to establish a mapping between the ac-tions performed by the expert and the steps suggested by the protocol. We discuss the reasons for this difficulty, and assess its consequences for the automation of the critiquing process. "
Duftschmid G, Miksch S, Gall W. Verification of temporal scheduling constraints in clinical practice guidelines. Artif Intell Med 2002 Jun;25(2):93-121.

[PubMed]    [Paper]

" In this paper, we focus on the detection of flaws within temporal scheduling constraints. Temporal scheduling constraints are important elements of therapy management, and are frequently incorporated in clinical practice guidelines. We present a suitable verification method that is based on calculating the minimal network of temporal constraints on the execution of guideline activities.... Although we concentrate on the guideline representation language Asbru as the demonstration medium of our method within this paper, our approach can be reused to verify several alternative guideline representation formats. "
references: Asbru visualisation tools

Seyfang, A., Miksch, S., Conde, C. P., Wittenberg, J., Marcos, M. and Rosenbrand, K. (2005). A Many-Headed Bridge between Informal and Formal Guideline Representations. Proc. 10th Conf Artificial Intelligence in Medicine (AIME), in press.

[]   []

" Clinical guidelines become more and more important as a means to improve the quality of care by supporting the medical staff. Modeling guidelines in a computer-processable form is a prerequisite for various computer applications, to improve the quality of guidelines and to support their application. However, transforming the original text into a formal guideline representation is a difficult task requiring both computer scientist skills and medical knowledge. To bridge this gap, we designed an intermediate representation named MHB. "

W. Aigner, S. Miksch. CareVis: Integrated Visualization of Computerized Protocols and Temporal Patient Data. Presentation: Workshop on Intelligent Data Analyis in Medicine and Pharmacology (IDAMAP-2004), Stanford, USA; 06-09-2004; in: "Workshop Notes of the Workshop on Intelligent Data Analyis in Medicine and Pharmacology", (2004), ISBN 961-6209-47-7.

[]   [Vienna University of Technology]

" Currently, visualization support for patient data analysis is mostly limited to the representation of directly measured data. Contextual information on performed treatment steps is an important source for finding reasons and explanations for certain phenomena in the measured patient data. But this kind of information is mostly spared out in the analysis process. We describe the development of CareVis – interactive visualization methods to integrate and combine classical data visualization with the visualization of treatment information in terms of logic and temporal aspects. We provide multiple simultaneous views to cover different aspects of a complex underlying data structure of treatment plans and patient data. The tightly coupled views use visualization methods well-known to domain experts and are designed to facilitate users’ tasks. The views are based on the concepts of clinical algorithm maps and LifeLines which have been extended in order to cope with the powerful and expressive plan representation language Asbru. The user-centered development approach applied for these interactive visualization methods has been guided by user input gathered via a user study, design reviews, and prototype evaluations. "

W. Aigner, S. Miksch: "Supporting Protocol-Based Care in Medicine via Multiple Coordinated Views"; Presentation: CMV: 2nd International Conference on Coordinated and Multiple Views in Exploratory Visualization, IEEE, London, UK; 07-13-2004; in: "Proceedings International Conference on Coordinated and Multiple Views in Exploratory Visualization (CMV 2004)", IEEE, (2004), ISBN 0-7695-2179-7; 118 - 129.

[]   [Vienna University of Technology]

" Computer supported protocol-based care aims to aid physicians in the treatment process. The main focus of current research is directed towards the formal methods and representations used “behind the scenes” of such systems. This work on the contrary, is situated at the human end of the human-machine chain. We describe the development of interactive visualization methods to support protocol-based care. We provide multiple simultaneous views to cover different aspects of a complex underlying data structure of treatment plans and patient data. The tightly coupled views use visualization methods well-known to domain experts and are designed to facilitate users’ tasks. The views are based on the concepts of clinical algorithm maps and LifeLines which have been extended in order to cope with the powerful and expressive plan representation language Asbru. The user-centered development approach applied for these interactive visualization methods has been guided by user input gathered via a user study, design reviews, and prototype evaluations. "

Kosara, R.; Miksch, S.; Hauser, H.: Focus and Context Taken Literally, IEEE Computer Graphics and its Applications, Special Issue: Information Visualization, pp. 22-29, 22(1), Jan.-Feb., 2002.

[Paper]

" Pointing out relevant information to a user is one application of focus+context techniques in information visualization. We present a method for doing this which uses selective blur to direct the user's attention. This method is based on the depth of field (DOF) effect used in photography and cinematography, and is therefore both familiar to users and perceptually effective. Because this method blurs objects based on their relevance rather than their distance, we call it Semantic Depth of Field (SDOF). We also present four example applications that use SDOF to show its usefulness in practice, and also provide details of a fast implementation that makes it possible to use blur in interactive applications. A short report on the results of a user study we performed is also given. "
Kosara R, Miksch S. Metaphors of Movement: A Visualization and User Interface for Time-Oriented, Skeletal Plans, Artificial Intelligence in Medicine, Special Issue: Information Visualization in Medicine, pp. 111-131, 22(2), 2001.

[PubMed]

[paper - AIM]
[U Vienna - Paper]

" Therapy planning plays an increasingly important role in the everyday work of physicians. Clinical protocols or guidelines are typically represented using flow-charts, decision tables, or plain text. These representations are badly suited, however, for complex medical procedures.One representation method that overcomes these problems is the language Asbru. But because Asbru has a LISP-like syntax (and also incorporates many concepts from computer science), it is not suitable for physicians.Therefore, we developed a visualization and user interface to deal with treatment plans expressed in Asbru. We use graphical metaphors to make the underlying concepts easier to grasp, employ glyphs to communicate complex temporal information and colors to make it possible to understand the connection between the two views (Topological View and Temporal View) available in the system.In this paper, we present the design ideas behind AsbruView, and discuss its usefulness based on the results of a usability study we performed with six physicians. "
Kosara, R.; Miksch, S.: Visualization Methods for Data Analysis and Planning in Medical Applications, International Journal of Medical Informatics, pp. 141-153, 68 (1-3), December 2002.

[Paper]

" Time plays an important role in medicine, both the past and the future. The medical history of a patient represents the past, which needs to be understood by the physician to make the right decisions. The past contains two different kinds of information: measured data (such as blood pressure) and incidents (such as seizures). Planning therapies, on the other hand, requires looking into the future to a certain extent. Visual representations exist for both the past and the future, and they are very useful for getting a better understanding of data or a plan. This paper surveys visualization techniques for both data analysis and planning, and compares them based on a number of criteria. "
Miksch, S., Kosara, R., Shahar, Y., and Johnson, P. AsbruView: Visualization of time-oriented, skeletal plans. In: The Fourth International Conference on Artificial Intelligence Planning Systems 1998 (AIPS-98) (Carnegie-Mellon University, Pittsburgh, Pennsylvania), AAAI Press, Menlo Park, CA, 11-18.

[SMI]   [U. Vienna]

" Skeletal plans are a powerful way to reuse existing domain-specific procedural knowledge. The main draw-backs are that the compositions and the interdependencies of different skeletal plans and their components are not lucid. The aim of this paper is to overcome these limitations and to present the visualization of time-oriented, skeletal plans. Within the Asgaard project, we have developed a time-oriented and intention-based language, called Asbru, to represent such skeletal plans. The Asbru syntax is defined in Backus-Naur form (BNF). Reading BNF or similar forms are next to impossible even for domain experts. We explored different representations and automated knowledge-acquisition tools. However, the domain experts did not accept any of these representations. Consequently, we investigated different metaphor graphics and ended up with a plan visualization utilizing the metaphors of "tracks" and "traffic" called AsbruView. We formatively evaluated different approaches of this plan visualization with physicians applying treatment protocols of mechanical ventilated newborn infants. "
references: Asbru in use

Marcos, M., Roomans, H., ten Teije, A. and van Harmelen, F. (2002). Improving medical protocols through formalisation: a case study. 6th Intl Conf Integrated Design & Process Technology.

[]   []

" Medical practice protocols or guidelines contain more or less precise recommendations to assist practitioners and patient decisions about appropriate health care for specific circumstances. In order to reach their potential benefits, protocols must fulfill strong quality requirements. Medical bodies worldwide have made efforts in this direction, but mostly using informal methods such as peer review of protocols. In this paper we present a different approach, namely the quality improvement of medical protocols through formalisation.

Currently, protocols are described using a combination of different formats, e.g. text, flow diagrams and tables. The underlying idea of our work is that making these descriptions more precise, with the help of a more formal language, will expose parts where the protocols are ambiguous, incomplete or even inconsistent. By pointing out these anomalous parts, we expect to obtain useful indications for the improvement of the protocols. This idea is widely acknowledged in fields like software engineering, where formal methods are used as a tool for early detection of specification and design errors, but has been largely unexplored for medical protocols.

The research question that we try to answer in this paper is: can formalisation contribute to improve the quality of medical protocols? To answer this question, we have carried out a case study on protocol formalisation. For this purpose, a choice had to be made on the specific protocol representation language as well as on the medical protocols to be used. Several languages exist for representing medical protocols. For our case study we need a sufficiently formal and detailed enough language since only precise descriptions will allow us to uncover anomalies in the protocols. We have chosen Asbru, firstly because it is more precise in the description of various medical aspects, and secondly because Asbru protocols are more declarative, and thus they are more amenable to formal analysis. Concerning the protocols, we have tried to select two examples covering different features. The first one is a protocol for the management of diabetes mellitus type 2, which comes from the set of protocols developed by the Dutch Association of General Practitioners. The second example is a pediatrics protocol for the management of jaundice in healthy newborns, developed by the American Academy of Pediatrics. "

Seyfang A, Miksch S, Marcos M. Combining diagnosis and treatment using Asbru. Int J Med Inform. 2002 Dec 18;68(1-3):49-57.

[PubMed]   [Vienna University of Technology]

" Traditionally, diagnosis and treatment have been seen as two distinct tasks. Consequently, most approaches to computer supported health care focus on one of the two-mostly on diagnosis or rather on the interpretation of measurements which is much better understood and formalised. However, in practice diagnosis and treatment overlap and influence each other in many ways. Combinations range from repeatedly going through the diagnosis-treatment loop over a period of time to permanent monitoring of the patients' health condition as it is done in intensive care units. In this article we describe how to model these combinations using the clinical protocol-representation language Asbru. It implements treatment steps in a hierarchy of skeletal, time-oriented plans. Diagnosis can either be described in a declarative way in the conditions, under which treatment steps are taken or it can be modelled explicitly as plans of their own right. We demonstrate our approach using examples taken from the American Association of Paediatricians' guideline for the treatment of hyperbilirubinemia in the new-born. "

references: technical documents
Seyfang, A.; Kosara, R.; Miksch S.: Asbru Reference Manual, Asbru Version 7.3, Vienna University of Technology, Institute of Software Technology and Interactive Systems, Vienna, Technical Report, Asgaard-TR-2002-1, 2002.

[Manual]

" "

contact Silvia Miksch
Institute of Software Technology and Interactive Systems
Vienna University of Technology
Favoritenstrasse 9-11/188
A-1040 Vienna
Austria

E: silvia@ifs.tuwien.ac.at

links  bullet  Asgaard project (Vienna)  bullet  The Asbru language - Vienna University of Technology  bullet  Asbru syntax (downloadable files)  bullet  Asgaard/Asbru (Stanford University)  bullet  AsbruView - Document Exploration and Linking Tool [OC]  bullet  DELT/A - Data and Plan Visualization [OC]  bullet  CareVis - Integrated Visualization of Computerized Protocols and Temporal Patient Data [OC]  bullet  Asbru Interpreter - guideline execution [OC]  bullet  DEGEL Digital electronic Guideline Library Framework [OC]  bullet  KNAVE II project [OC]  bullet  Protocure project [OC]  bullet  in2vis project [OC] in2vis  bullet  Presentation: Silvia Miksch. Asbru: A Task-Specific, Intention-Based, and Time-Oriented Language for Representing Skeletal Plans (presentation from OpenClinical one-day workshop, Methods for the Representation of Computer-Interpretable Clinical Guidelines, London, September 6 2001)
acknowledgements
Silvia Miksch, Vienna University of Technology & Danube University Krems, Austria
page history
Entry on OpenClinical: 2002
Last main updates: 03 September 2003; 24 May 2005

 

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