Using a combination of artificial intelligence and information engineering, Kirontech's coding engine allows us to process claims data even with incomplete or missing diagnosis, service or drug codes.
By using advanced NLP - based techniques, the coding engine can accurately suggest codes for conditions and services as long as descriptions are provided.
Whenever you act on the recommendations made by the Kirontech Platform, you will ask questions like: "Was this claim correctly flagged? Is this provider charging more for their services than they should? Is this provider a specialist in their field and therefore has a higher concentration of particular kind of treatment?"
The Platform allows the customer to quickly and conveniently give feedback on the decisions. As you provide feedback, you enforce desired behaviour. As you work, the system learns with you.
Kirontech medical semantic network (KironMed) collect data from more than 60 medical sources, combining it to form one of the most comprehensive reference networks in existence.
Our claim handling algorithms leverage these networks to help them learn and to ensure that our customers' claims data is enriched to the max.
Unsupervised learning identifies recurrent but previously unknown patterns in your data. The algorithm searches for abnormal associations without being told what to look for by a human being.
It can learn and adapt to new relevant patterns much faster than a human being and spot complicated relationships that are not visible to unaided eye.