CAIRN (Computer Assisted $\underbar{M}$edical Information Resource Navigation) is a prototyping System that allows flexible medical data storage and retrieval supporting medical informatics research. In this paper methods that automate the selection of ICD-9 diagnosis (International Classification of Diseases and Diagnoses, 9th Revision) are investigated. We present the Text Data Mining module extension of CAIRN and its application in order to organize in a systematic way uncontrolled terms, to propose relationships between uncontrolled terms and finally aid the diagnosis classification.