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 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 can build tables of events or facts in any domain required. For instance, a large industrial manufacturer uses ayfie to analyze incident reports about turbine malfunctions. While these reports are written in plain text by service personnel, ayfie is able to turn them into tabular structures:
Based on the tables created by ayfie, 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 would normally only be possible on pre-structured data.
We solve business problems with data analysis tailored to your needs by leveraging machine learning, linguistic analysis and years of experience solving complicated problems.