Abstract: A textual report generation method and system translating structured medical information into textual reports which can be customized in detail and vocabulary for different intended audiences. The structured data may exist in a pre-existing electronic medical record and/or be elicited from patients and medical professionals. Using the structured information, a disease signature is identified which, in turn, identifies the appropriate lexical domain and rules for generating a textual report describing the patient's condition. Context-free grammars are used with a system of rules corresponding to logical relations in the structured data to generate the textual reports.

Abstract: A natural language translation method and system translating medical reports created in natural language into structured data frames that can be utilized in computer databases for decision support, billing, research, and other purposes. Structured data entry is elicited from a patient in order to identify an appropriate disease signature corresponding to his or her condition and symptoms. In turn, the disease signature identifies the appropriate lexical domain with which to analyze the natural language report. The translation method and system use statistical analysis based on empirical data that particular combinations of words have interdepended previously within a modeled context and how frequently individual words interdepend generally and with what kinds of words. For each sentence in the report, the words in the medical report are looked up in the lexical domain individually and in combination with all other words coexisting in the same sentence.