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A neural network expert system to support decisions in diagnostic mapping
By: Roesner, D.; Kuhn, K.; Ditschuneit, H.; Doster, W.; Reichert, M.; Heinlein, C.; Wechsler, J.G.; Janowitz, P.; Swobodnik, W.; Zemmler, T.;
1991 / IEEE / 0-8186-2164-8
Description
This item was taken from the IEEE Periodical ' A neural network expert system to support decisions in diagnostic mapping ' An expert system module has been integrated into clinical workstations used for report generation and the storage and retrieval of diagnostic images. The expert system works in the background and supports the physician's decisions. The system has been created for ultrasound examinations of the abdomen. The knowledge-based system has been implemented for the same knowledge segment using two different methods: a rule-based approach with the AI-tool Joshua on a Symbolics machine for prototyping and knowledge debugging and a neural network approach based on back propagation. The results show that the neural network is robust and flexible for the mainly associative knowledge found in this application; it performed well in general and, specifically, on subsets of findings entered during the course of an examination. It was therefore decided to combine both components.<
Related Topics
Clinical Workstations
Diagnostic Images
Ultrasound Examinations
Abdomen
Knowledge-based System
Rule-based Approach
Ai-tool Joshua
Symbolics Machine
Prototyping
Knowledge Debugging
Neural Network Approach
Back Propagation
Neural Networks
Diagnostic Expert Systems
Image Storage
Workstations
Image Retrieval
Ultrasonic Imaging
Abdomen
Knowledge Based Systems
Image Segmentation
Prototypes
Expert System Module
Diagnostic Mapping
Decisions
Neural Network Expert System
Associative Knowledge
Medical Diagnostic Computing
Expert Systems
Decision Support Systems
Computerised Picture Processing
Neural Nets
Engineering
Report Generation