A causal model of blood enzyme data and visualization of tissue conditions

Quantitative diagnostics is an important field in which clinical data are converted into medical information. A variety of approaches to obtain medical diagnoses have been developed and multivariate statistical analysis supports the diagnostic process. Although many clinical data are affected by body conditions such as disease and functional failure, only a few models take this phenomenon into consideration. The correlation between laboratory test results can be understood as a causal relationship between body conditions and clinical test data variations. A multivariate statistical method, factor analysis, expresses a causal relationship between latent variables and observed variables. We developed a causal model for blood enzyme data using factor analysis. The latent variables were assumed to be organ specific regarding 9 enzyme data. This causal model expressed clinical knowledge within blood enzymes and allowed visualization of organ conditions. The visualization of laboratory data is useful to screen patient's pathological states.