Architecture-Level Dependability Analysis of a Medical Decision Support System
Conference
·
OSTI ID:981430
- ORNL
Recent advances in techniques such as image analysis, text analysis and machine learning have shown great potential to assist physicians in detecting and diagnosing health issues in patients. In this paper, we describe the approach and findings of an architecture-level dependability analysis for a mammography decision support system that incorporates these techniques. The goal of the research described in this paper is to provide an initial understanding of the dependability issues, particularly the potential failure modes and severity, in order to identify areas of potential high risk. The results will guide design decisions and provide the basis of a dependability and performance evaluation program.
- Research Organization:
- Oak Ridge National Laboratory (ORNL)
- Sponsoring Organization:
- ORNL LDRD Director's R&D
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 981430
- Country of Publication:
- United States
- Language:
- English
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