GAIT-ER-AID: An expert system for diagnosis of human gait

Authors:
George A. Bekey;Joung-woo J. Kim;JoAnne K. Gronley;Ernest L. Bontrager;Jacquelin Perry
Affiliations:
Computer Science Department, University of Southern California, Los Angeles, CA 90089, USA;Computer Science Department, University of Southern California, Los Angeles, CA 90089, USA;Pathokinesiology Laboratory, Rancho Los Amigos Medical Center, Downey, CA 90242, USA;Pathokinesiology Laboratory, Rancho Los Amigos Medical Center, Downey, CA 90242, USA;Pathokinesiology Laboratory, Rancho Los Amigos Medical Center, Downey, CA 90242, USA
Venue:
Artificial Intelligence in Medicine
Year:
1992

Citing 2
Cited 0

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Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)
A computational model for causal and diagnostic reasoning in inference systems

IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1

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Abstract

A general knowledge-based system for diagnosis of human gait pathologies is presented. Gait analysis is a non-trivial medical diagnosis problem which involves a vast amount of data and complex reasoning. By capturing an expert's diagnostic knowledge compactly in diagnostic reference frames, the system expedites decision making from large and heterogeneous data sets. The variability of the data as well as its complexity dictated a 'divide and conquer', modular inferencing strategy, using only partial data and pruning the tree of potential diagnoses at each step. The concluding section of the paper presents our plans for augmentation of the system by making use of model-based qualitative reasoning to handle cases not currently in the knowledge base.