In this world of ever-increasing volume and variety of textual data, there is a growing variety of tools and technologies to handle and get value from these data.  We hear about a potentially bewildering barrage of AI technologies including Natural Language Processing (NLP), Machine learning, and other textual data science applications. A recent blog I read highlighted this, with a Venn covering over a dozen different disciplines (see figure below). These techniques all bring benefits, but often we just need straightforward simple access to our unstructured text data.

Empower a wide variety of users to find relevant data with high recall and precision

Linguamatics I2E brings a combination of powerful text mining tools to many pharma, biotech and healthcare users. We recognize that users’ -demands vary, and so we have created I2E Web Portals. I2E Web portals aim to engage users that want rapid easy access to scientific knowledge from both public domain knowledgebase (e.g. MEDLINE, ClinicalTrials.gov) and internal data silos, ranging from regulatory dossiers, preclinical safety data, patient/customer call transcripts, and many more.


Linguamatics I2E 5.2.0 was released at the beginning of October with availability for Enterprise and OnDemand users. It was hot on the heels of our I2E 5.1 release: we’re speeding the I2E release cycle up to release quarterly, so that you can access the latest I2E features faster.

With I2E 5.2.0, your indexes and queries are now organized in trees, which combine content stored locally and remotely i.e. on the cloud. And now it’s easier to find them: the tree views are dynamically filtered when you type the name of your index or query into the search box.

Our HTML results have had a refresh! Making it easier for you to quickly review your results and only show more advanced options when you need them.

Getting to the correct classes quickly is a key part of any query building, so in I2E 5.2.0, we made class matching up to 5x faster across I2E Pro, I2E Express, web portals and custom interfaces.

I2E 5.2.0 was launched at TMS, and everyone who took part in the workshops got a chance to use these new features and improvements in sessions such as the Query Hackathon and Leveraging New I2E Features.

Find out more about what's new in I2E.


November always brings to mind Thanksgiving and turkey, but for those of us in medical informatics it means it’s time for AMIA’s national symposium and this time it is back in Washington DC. With political upheaval in healthcare and the opioid epidemic making headlines across the nation there will be no shortage of talking points. AMIA brings together some of the best and the brightest minds in medical informatics and a great place to engage with each other to highlight opportunities for IT to improve the lives of Americans with technology.

This will be my fifth time going to AMIA, a relative novice compared to many, but I find the scale of this event much more palatable than the behemoth that is HIMSS, with a more forward-looking vibe. Linguamatics have many events planned for AMIA this year, including a pre-symposium talk, a presentation on physician metrics by MUSC and a Learning Showcase presentation. Check out the details below and stop by and see us at booth #205.

Using Text Mining to Identify Risk of Opioid Medication Abuse

Presented by Erin Tavano, Clinical Data Scientist, Linguamatics

8:30AM – 4:30PM, Saturday November 4, 2017, Georgetown East


Media reports on the opioid abuse crisis in the U.S. increasingly dominate our TV screens and news feeds. But when do we start recognizing these statistics as actual people in need of help—what if we can identify at-risk individuals while they still have options?

Early recognition of opioid misuse is key to identifying people at risk and getting them timely treatment, but those “dancing with the devil” are hard to find in the early stages, and rarely come forward on their own.

In an article for HITECH Answers, Linguamatics’ Dr. Elizabeth Marshall reflects on how the crisis has affected her on a personal level. She looks at how using natural language processing (NLP) to analyze structured and unstructured data from sources such as clinician notes could help identify patterns that reveal possible opioid abuse. Dr. Marshall also suggests further measures that organizations, institutions, and communities might take to combat this growing epidemic.

Read the full article here.


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: