Project-4: Named Entity Recognition - Clinical Data Extraction
Named Entity Recognition (NER) — also referred to as named entity extraction or identification — is an extraction technique that automatically identifies key information from text data and classifies them into predefined categories. It is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organisations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc. In this article we will take example of clincal data and discuss how a NER model can be built using SpaCy and relevant entities are extracted as per the requirement.