The electronic medical record (EMR) in combat medical data repositories can contain a vast amount of unstructured free text that record the history, diagnoses, and treatments of patients suffering injuries and illnesses on the battlefield. These unstructured data are typically recorded by clinicians at medical treatment facilities, or by experienced medical coders, summarizing patient diagnosis and treatment. Examples of unstructured data are the Subjective, Objective, Assessment, and Plan of Care fields that can contain up to 4,000 bytes of data in each EMR in the Theater Medical Data Store repository. To date, little or no analysis has been done on the unstructured data in the combat EMR. This presentation demonstrates the application of current, state-of-the-art text mining methods to extract useful information from free text data within the EMR.