In the same manner, doctors use many different expressions, ranging from colloquial to very formal, in describing obesity in patient notes. ayfie understands all of these variations and can map them to the correct ICD 10 code.
For dealing with structure extraction and semantics, ayfie Inspector builds on well-researched linguistic frameworks based on the works of Zelig Harris, Maurice Gross and Franz Guenthner. This sound theoretical foundation is combined with our blazingly fast proprietary extraction engine and exhaustive resources in many languages and domains.
By aggregating extracted predicates of the same type, ayfie Inspector can build tables of events or facts in any domain required. For example, a large industrial manufacturer uses ayfie Inspector to analyze incident reports about turbine malfunctions. Service personnel write their reports in natural language, and ayfie Inspector turns them into structured, tabular content:
Based on the tables created by ayfie Inspector, the manufacturing company can now precisely answer questions like:
"Which part failed most often because of outside heat?"
"Which malfunction is the most likely for a certain class of parts?"
"Which environmental conditions are the most detrimental to the overall reliability of the component?"
Thus, all free-text service reports and even historical texts can be subjected to rigid analyses that were once impossible without time-consuming and expensive data transformation projects.
Extracting Insight from Unstructured Content
We solve business problems with data analysis tailored to your needs by leveraging natural language processing, guided machine learning, linguistic analysis and years of experience. Ready to start seeing value from your content?