Temporal modelling of medical events

Many medical events are buried in the notes made by the doctors in multiple documents and many of them have only partial descriptions. We identified medically significant events like ‘infections’, ‘antibiotics’, ‘surgery’, ‘x-ray’, ‘lab test’ etc. Used NLP to arrive at the occurrence time of significant events by identifying temporal expressions like ‘today’, ‘two weeks ago’ etc. extracted from the multiple
documents and correlating them with the date of document creation. We then stored this data in a structured repository for easy retrieval to construct the time line graph of the significant clinical events.