Cluster-oriented discriminant analysis; taxonomic classification of the thyroid function.
A computer assisted procedure for the diagnosis of thyroid diseases, based on seven clinical chemical parameters, is proposed. The population studied consisted of 592 consecutive outpatients with a tentative diagnosis of thyroid disease. Thyroxine, triiodothyronine, T3 uptake test, TSH before and after TRH application, its difference and thyroxine binding globulin have been determined. The patients were clinically examined and in each case a Tc-scintigram was obtained. As a first step, 20 biochemical patterns were defined by cluster analysis (pattern cognition). T check how good in grouping process was, linear discriminant analysis was applied after which the reclassification rates were very satisfactory. The clusters found corresponded well to the pathophysiological situations with some exceptions. As a second step, patients were assigned to these patterns by use of the derived discriminant functions (pattern recognition). The proposed method seems to have some advantages over other diagnostic models published hitherto.
D000510:Alpha-Globulins / Q000378:metabolism; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D013223:Statistics as Topic; D013959:Thyroid Diseases / Q000175:diagnosis*; D013972:Thyrotropin / Q000097:blood; D013973:Thyrotropin-Releasing Hormone; D013974:Thyroxine / Q000097:blood; D013975:Thyroxine-Binding Proteins / Q000378:metabolism; D014284:Triiodothyronine / Q000097:blood
D000510:Alpha-Globulins; D013975:Thyroxine-Binding Proteins; D014284:Triiodothyronine; D013973:Thyrotropin-Releasing Hormone; D013972:Thyrotropin; D013974:Thyroxine