Acquisition and Analysis of Repeating Patterns in Time-oriented Clinical Data

Summary

Objectives: (1) Creation of an expressive language for specification of temporal patterns in clinical domains, (2) Development of a graphical knowledge-acquisition tool allowing expert physicians to define meaningful domain-specific patterns, (3) Implementation of an interpreter capable of detecting such patterns in clinical databases, and (4) Evaluation of the tools in the domains of diabetes and oncology.

Methods: We describe a constraint-based language, named CAPSUL, for specification of temporal patterns. We implemented a knowledge-acquisition tool and a temporal-pattern interpreter within Résumé, a larger temporal-abstraction architecture. We evaluated the knowledge-acquisition process with the help of domain experts. In collaboration with the Rush Presbyterian/St. Luke’s Medical Center, we analyzed data of bone-marrow transplantation patients. The expert compared the detected patterns to a manual inspection of the data, with the help of an experimental information-visualization tool we are developing in a related project.

Results: The CAPSUL language was expressive enough during the knowledge-acquisition process to capture almost all of the patterns that the experts found useful. The patterns detected in the data by the pattern interpreter were all verified as correct. Completeness (whether all correct patterns were found) was difficult to assess, due to the size of the database.

Conclusions: The CAPSUL language enables medical experts to express temporal patterns involving multiple levels of abstraction of clinical data. The ability to reuse both domain-patterns and abstract constraints seems highly useful. The Résumé interpreter, augmented by the CAPSUL semantics, finds the complex patterns within a clinical time-oriented database in a sound fashion.

Keywords

Temporal Reasoning - Pattern Matching - Temporal Abstraction - Periodicity

• References

• 1 Shahar Y, Musen M. Knowledge-based temporal abstraction in clinical domains. Artif Intell Med 1996; 8 (Suppl. 03) 267-98.
• 2 Shahar Y. A framework for knowledge-based temporal abstraction. Artificial Intelligence 1997; 90 1-2 79-133.
• 3 Shahar Y. Dynamic Temporal Interpretation Contexts for temporal abstraction. Annals of Mathematics and Artificial Intelligence 1998; 22 1-2 159-92.
• 4 Musen MA, Tu SW, Das AK, Shahar Y. EON:A component-based approach to automation of protocol-directed therapy. JAMA 1996; 3 (Suppl. 06) 367-88.
• 5 Shahar Y, Cheng C. Intelligent Visualization and Exploration of Time-Oriented Clinical Data. In press for Topics in Health Information Management (THIM) 1999
• 6 Ladkin P. Time representation: A taxonomy of interval relations. In: Proceedings of the AAAI-86. 1986: 360-6.
• 7 Allen J. Towards a general theory of action and time. Artificial Intelligence 1984; 23 (Suppl. 02) 123-54.
• 8 Chakravarty S, Shahar Y. A constraint-based specification of periodic patterns in time-oriented data. In: Proceedings of the International Workshop on Temporal Representation and Reasoning (Time)-99. IEEE Press; 1999: 29-40.
• 9 Shahar Y, Chen H, Stites DP, Basso L, Kaizer H, Wilson DM, Musen MA. Semiautomated Acquisition of Clinical Temporal-abstraction Knowledge. In press for Journal of the American Medical Informatics Association (JAMIA) 6 (Suppl. 06) 99.
• 10 Ladkin P. Primitives and Units for Time Specification. In: Proceedings of the AAAI-86. 1996: 354-9.
• 11 Clifford J, Rao A. A simple, general structure for temporal domains. Temporal Aspects in Information Systems, IFIP. 1988: 17-28.
• 12 Cukierman D, Delgrande J. Characterizing Temporal Repetition. In: Proceedings of the International Workshop on Temporal Reasoning and Representation (TIME)-96. IEEE Press; 1996: 80-7.
• 13 Cukierman D, Delgrande J. Towards a formal characterization of temporal repetition with closed time. In: Proceedings of the International Workshop on Temporal Reasoning and Representation (TIME)-98. IEEE Press; 1998: 140-7.
• 14 Terenziani P. Qualitative and Quantitative Temporal Constraints About Numerically Quantified Periodic Events. In: Proceedings of the International Workshop on Temporal Reasoning and Representation (TIME)-97. IEEE Press; 1997: 94-101.
• 15 Morris R, Khatib L. Quantitative Structural Temporal Constraints on Repeating Events. In: Proceedings of the International Workshop on Temporal Reasoning and Representation (TIME)-98. IEEE Press; 1998: 74-9.
• 16 Morris R, Khatib L. Periodic and Repeating Events. Florida Institute of Technology; 1996: 1-17.
• 17 Khatib L. Reasoning with Non-convex Time Intervals. PhD. Thesis. Florida Institute of Technology; 1994