Evaluation of a semantic data model for chest radiology: application of a new methodology.

An essential step toward the effective processing of the medical language is the development of representational models that formalize the language semantics. These models, also known as semantic data models, help to unlock the meaning of descriptive expressions, making them accessible to computer systems. The present study tries to determine the quality of a semantic data model created to encode chest radiology findings. The evaluation methodology relied on the ability of physicians to extract information from textual and encoded representations of chest X-ray reports, whilst answering questions associated with each report. The evaluation demonstrated that the encoded reports seemed to have the same information content of the original textual reports. The methodology generated useful data regarding the quality of the data model, demonstrating that certain segments were creating ambiguous representations and that some details were not being represented.