A short-form measure of user information satisfaction: a psychometric evaluation and notes on use
Journal of Management Information Systems
Case-based reasoning: a research paradigm
AI Magazine
Case-based reasoning: business applications
Communications of the ACM
Case-based reasoning for intelligent support of construction negotiation
Information and Management
Decision support for healthcare in a new information age
Decision Support Systems
A case-based approach using inductive indexing for corporate bond rating
Decision Support Systems - Decision-making and E-commerce systems
Integrating Case-Based Reasoning and Decision Theory
IEEE Expert: Intelligent Systems and Their Applications
Analysis on risk factors for cervical cancer using induction technique
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural
Expert Systems with Applications: An International Journal
Formulating strategies for stakeholder management: a case-based reasoning approach
Expert Systems with Applications: An International Journal
Case representation ontology for case retrieval systems in medical domains
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Severity Evaluation Support for Burns Unit Patients Based on Temporal Episodic Knowledge Retrieval
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
Ontology-based mammography annotation and Case-based Retrieval of breast masses
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
Mammography is an important screening tool for early detection of breast cancer. However, radiologists usually experience difficulties in image interpretation of grey zones. A computer system providing similar cases with known diagnostic results for decision support would be useful. Applying case-based reasoning (CBR) to a mammographic case base, constructed from prior cases with known diagnostic results, offers a solution to this problem. Serving as an inference tool, the CBR can retrieve similar cases to help radiologists interpret a new mammographic case. To evaluate the usability of this system, 34 licensed radiologists were invited as experts to assess the system. The results indicate that CBR applied to the mammographic case base is valuable for decision support in mammographic image interpretation.