Abstract
This paper describes a computational model developed for the diagnosis of multiple defects. If multiple defects interact, meaning that the cues observable for multiple defects are not a sum of the cues observable for the component defects, diagnosis is particularly difficult. We developed a description and classification of the ways cues change when defects interact. A computational model (named Fallot) was implemented and a knowledge-base was constructed for the diagnosis of congenital heart defects. On each case, Fallot performs recognition-based reasoning followed by solution construction and evaluation with the cue combination methods. Fallot was tested on cases from hospital files and correctly diagnoses cases with multiple interacting defects for which conventional methods are not applicable or fail.
Original language | English (US) |
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Pages (from-to) | 25-40 |
Number of pages | 16 |
Journal | Artificial Intelligence in Medicine |
Volume | 10 |
Issue number | 1 |
DOIs | |
State | Published - May 1997 |
Keywords
- Cardiology
- Diagnosis
- Expert systems
- Multiple defects or diseases