Use of a microcomputer for the definition of multivariate confidence regions in medical diagnosis based on clinical laboratory profiles.

The use of multivariate confidence regions is proposed for the classification of clinical laboratory profiles into diagnostic classes. For this purpose, a multivariate confidence region is developed for each diagnostic class. Three methods (UNEQ, EQ, and SIMCA) are evaluated and compared with classical linear discriminant analysis. As an example, a small data set concerning the differentiation of the thyroid functional states on the basis of five laboratory tests is used. It is shown that related procedures can produce results of very different quality and that the multivariate region approach is attractive for the clinician's daily practice since the methods are easily implemented on a microcomputer.