Rapid evaluation of human biomonitoring data using pattern recognition systems.

Assessing human biomonitoring data often necessitates dealing with fragmentary prior knowledge and a complex set of variables. A procedure for explorative data analysis via decision-tree analysis was undertaken to obtain high-level descriptive summary information on human exposure on a timely basis. This study is based on a subset of monitoring data of the Environmental Specimen Bank for Human Tissues within the German Environmental Specimen Bank (n sigma: 2401: 42/58% males/females; 34/66% born in East/West Germany).

The Environmental Specimen Bank for Human Tissues as part of the German Environmental Specimen Bank.

The German Environmental Specimen Bank for Human Tissues (ESBHum) as part of the German Environmental Specimen Bank (ESB) focuses on documenting and assessing trends of human exposure via real-time monitoring of body burden and long-term storage of samples under stable deep freezing conditions (-150 degrees C) for later retrospective analyses. Real-time monitoring is performed after completing sampling processes of one year and covers actually 20 inorganic and 5 organic substances. While concentrations of several substances, e.