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Complex Measurement Classification in Medical Applications Using a Case-Based Approach


ISSN 1503-416X

Publication Type:

Conference/Workshop Paper


ICCBR03 - The Fifth International Conference on Case-Based Reasoning - Workshop proceedings




In many domains it is sufficient to classify measurements obtained by sensors by filtering noisy data and performing a classification of the measure-ments by means of some mathematical function. Classification of measurements is difficult in some medical domains, e.g. determination of stress levels. Measurements and their classification may be too complex for an algorithmic approach. Matching may result in a number of classification candidates, historic data (previously classified measurements) may be sparse, and same measurements may indicate several diagnoses. We propose a Case-Based Reasoning approach in which feature vectors are matched against cases in a case library, and in which indeterministic or weak classifications are validated by an experienced physician, pointing out the features relevant in the classification of psychophysiological dysfunctions. The physician’s classifications are stored in the case library, continuously improving the system’s performance as it is being used. If only a few examples of classified measurements are available, the experienced physician initially points out which feature combinations are used in the classification/diagnosis.


author = {Markus Nilsson and Peter Funk and Mikael Sollenborn},
title = {Complex Measurement Classification in Medical Applications Using a Case-Based Approach},
note = {ISSN 1503-416X},
editor = {Lorraine McGinty},
pages = {63--73},
month = {June},
year = {2003},
booktitle = {ICCBR03 - The Fifth International Conference on Case-Based Reasoning - Workshop proceedings},
publisher = {Springer},
url = {}