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Title: Architecture-Level Dependability Analysis of a Medical Decision Support System

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.
Authors:
 [1] ;  [1] ;  [1] ;  [1]
  1. ORNL
Publication Date:
OSTI Identifier:
981430
DOE Contract Number:
DE-AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: Software Engineering in Health Care (workshop associated with Intl Conf on Software Engineering), Cape Town, South Africa, 20100503, 20100508
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Laboratory Directed Research and Development (LDRD) Program
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; DESIGN; ENGINEERING; EVALUATION; FAILURES; IMAGES; LEARNING; ORDERS; PATIENTS; PERFORMANCE; POTENTIALS