Linguamatics I2E takes NLP Text Mining to New Heights
Last week I was at the Linguamatics Text Mining Summit – for a feast of new experiences. The Summit was hosted at Wentworth-by-the-Sea, a new venue for the TMS, and it was a wonderful showcase for 3 days of workshops, round table discussions, and talks.
In addition to a new location, the attendees learned about fresh ways of approaching challenges across both life science and healthcare. Some of the innovations came from the recently released features of I2E 5.2, many others from our customers.
A relatively new use of Natural Language Processing (a well-established AI technology), is to power machine learning (ML). David Milward (Linguamatics) discussed how I2E both utilises ML and can also effectively feed ML workflows with high quality data. Simon Beaulah (Linguamatics) gave an overview of new applications of I2E NLP in healthcare; several of which involve using NLP to fuel ML models. These include predicting 30-day readmissions; extraction of cardiac risk factors; or patient stratification of heart failure risk from echocardiogram metrics.
A broad range of NLP Text Analytics Applications across Life Science and Healthcare
Using text mining for ETL (extract transform and load) is becoming more widespread. Several of our customers talked about the power of NLP to extract structured data from unstructured text, and load the results into databases, warehouses or data lakes for broader access and decision support: