The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
EON: A Component-Based Approach to Automation of Protocol-Directed Therapy
Open accessAbstract
Provision of automated support for planning protocol-directed therapy requires a computer program to take as input clinical data stored in an electronic patient-record system and to generate as output recommendations for therapeutic interventions and laboratory testing that are defined by applicable protocols. This paper presents a synthesis of research carried out at Stanford University to model the therapy-planning task and to demonstrate a component-based architecture for building protocol-based decision-support systems. We have constructed general-purpose software components that (1) interpret abstract protocol specifications to construct appropriate patient-specific treatment plans; (2) infer from time-stamped patient data higher-level, interval-based, abstract concepts; (3) perform time-oriented queries on a time-oriented patient database; and (4) allow acquisition and maintenance of protocol knowledge in a manner that facilitates efficient processing both by humans and by computers. We have implemented these components in a computer system known as EON. Each of the components has been developed, evaluated, and reported independently. We have evaluated the integration of the components as a composite architecture by implementing T-HELPER, a computer-based patient-record system that uses EON to offer advice regarding the management of patients who are following clinical trial protocols for AIDS or HIV infection. A test of the reuse of the software components in a different clinical domain demonstrated rapid development of a prototype application to support protocol-based care of patients who have breast cancer.
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Cites
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Dimensions of knowledge sharing and reuse
Musen, M. A. (1992) · Computers and Biomedical Research · doi:10.1016/0010-4809(92)90003-s · Cited by 351
Self-citationKnowledge-based temporal abstraction in clinical domains
Shahar, Y., & Musen, M. A. (1996) · Artificial Intelligence in Medicine · doi:10.1016/0933-3657(95)00036-4 · Cited by 313
Self-citationRationale for the Arden Syntax
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Temporal logics in AI: Semantical and ontological considerations
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Concepts, attributes and arbitrary relations
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Temporal abstraction in intelligent clinical data analysis: A survey
Stacey, M., & McGregor, C. (2007) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2006.08.002 · Cited by 146
CDSS-RM: a clinical decision support system reference model
Zikos, D., & DeLellis, N. (2018) · BMC Medical Research Methodology · doi:10.1186/s12874-018-0587-6 · Cited by 78
The AI Future of Emergency Medicine
Petrella, R. J. (2024) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2024.01.031 · Cited by 43
Metadata
- Authors
- Musen, M. A., Tu, S. W., Das, A. K., & Shahar, Y.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 1996-11-01
- Volume
- 3
- Issue
- 6
- Pages
- 367-388
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- OpenAlex
- W2130455574
- Cited by
- 346
- References
- 35
- FWCI
- 52.86
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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