Constructing the correct diagnosis when symptoms disappear

• Authors: Nancy E. Reed
• Venue: AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
• Year: 1998

When multiple defects (also called diseases or faults) are present, there is a possibility of interactions between the defects. When defects interact, the cues (data obtainable) for a combination of defects is not a simple sum of the cues observable for the component defects. Expected cues may be missing, altered, or new cues may appear. Each of these alterations of cues makes diagnosis more difficult, as the correct defect combination may not even be considered (triggered) by a diagnostic system. We present an algorithm for heuristic solution construction that integrates multiple types of information about the case. Solutions are evaluated based on how many of the abnormal cues are accounted for, with a method that combines cues that may be altered due to interactions between defects. The method can account for cues that combine with one another in three basic ways, set union, additively and ordered dominance (some values mask other values) or with a combination of those basic ways.For the solution space of one task, diagnosing congenital heart defects, we considered seven major defects and found the solution space (exhaustive) was reduced by approximately 50% because some of the defects could not physically occur together. Experimental results on cases from hospital files demonstrate the effectiveness of the heuristic solution construction algorithm to generate the correct solution early which reduced the number of solutions explored (compared to an exhaustive search) even further on most cases. With the computational power of current workstations, even cases requiring exploration of this entire solution space required less than 4 minutes of CPU time per case.