Medical Record Mapping

It’s essential that medical geneticists know what the latest updates and findings are within their domain. This gives physicians security in their decision making because they know they are supported by the latest knowledge developments in that area, for which many relevant publications are made available each month. It also means that state of the art assertions can be made – resulting in correct diagnoses and better treatment and analysis.

The solution here involves several steps, all of which are detailed - including the frameworks - in the publication linked below. It starts with  constructing an information integration based on relevant entities and relationships from biomedical literature and then mapping these to an actual medical record. Outputs include a mini ontology graph, which can be leveraged by external applications, as well as being able to infer new relations.

⇒ Download Workflow from KNIME Hub

With KNIME Analytics Platform all tasks could be done within one visual environment. It was easy to read in the different data sources and the machine learning functionality such as the classification nodes enabled non-coders and programmers to work independently and efficiently. In addition, the KNIME Textprocessing Extension provided all the functionality needed for natural language programming nodes such as POS Tagger and Entity Recognition.

⇒ Download this Innovation Note as a PDF

This Innovation Note was written by KNIME community member Fernando López Bello as part of his Bioinformatics Masters Thesis. Read the full publication.