We are always amazed and impressed at the inventiveness of Linguamatics customers, in their applications of text analytics to address their information challenges.

Our annual Linguamatics Spring Users Conference showcased some examples of their innovation, with presentations on text mining used for patent analytics, chemical pharmacokinetics and pharmacodynamics data extraction, creating value from legacy safety reports, and integrating open source tools for advanced entity recognition.

We had a record-breaking number of attendees this year, representing over 20 organizations, ranging from our most experienced I2E users to text mining novices.
 

A record-breaking number of attendees enjoyed the opportunity to experience Cambridge and share insights with one another at this year's conference.

Patent analytics featured in two of the presentations, demonstrating the value of NLP in extracting critical information from obtuse and lengthy patent documents.

Julia Heinrich (Senior Patent Analyst, Biotechnology at Bristol-Myers Squibb, Princeton, New Jersey) asked the question: “Can the infoglut of biotech patent publications be quickly reviewed to enable timely business decisions?”.


(Cambridge, UK and Boston, USA – March 31, 2015) Linguamatics announces the latest release of its award-winning natural language processing (NLP)-based text mining and analytics platform I2E. I2E 4.3’s Connected Data Technology uses an innovative federated text mining architecture, allowing information extraction from multiple data sources at once.

Textual data is heterogeneous in format and often exists in silos spread across multiple locations. Instead of having to run many text mining queries separately across disparate data sources, I2E’s Connected Data Technology allows users to run a single query simultaneously over multiple data sources whether they are located locally, on Linguamatics’ cloud-based I2E OnDemand platform, or on third party servers elsewhere in the cloud. Results are merged together as a single results set that is sorted and clustered, ready for analysis. The technology allows users to get more comprehensive answers to their business critical questions by extracting, synthesizing and connecting all the relevant knowledge from each data source for faster analysis, leading to better decision support and increased speed to actionable insight.

Jason Stamper, Analyst at 451 Research, comments "The federated architecture I2E 4.3 uses is game-changing for knowledge driven industries like life sciences and healthcare. Access to data is a key part of their requirements for comprehensive results and this approach opens the door for organizations to get better results, faster and also allows third party providers of data to keep control of their content. I look forward to seeing how Linguamatics moves forward in the future and how this impacts their business.”


This year, Linguamatics returned to the beautiful town of Newport, Rhode Island, for our annual Text Mining Summit on October 13-15.

We were delighted to return to this exquisite setting, where again delegates competed over who could take the most beautiful sunrise and sunset photos.
 

Sunrise outside the Hyatt Regency, Newport, RI, Linguamatics Text Mining Summit 2014

Sunset captured at the Linguamatics Text Mining Summit 2014

The Text Mining Summit offers unique opportunities to learn about the latest use cases of Natural Language Processing (NLP) text analytics across pharma and healthcare, plus hands-on training, networking and idea sharing.

We hosted a fantastic line up of presenters from Novartis, Bristol-Myers Squibb, Georgetown University Medical Center, Spartanburg Regional Healthcare System, Boehringer Ingelheim, Pfizer, Cell Signalling Technology, Thomson Reuters, GenoSpace and Microsoft.

Mark Burfoot, Global Head, Knowledge Office for Novartis kicked off the proceedings on Tuesday with a keynote talk looking at the future of text mining and knowledge strategy within an evolving pharma landscape.


Natural Language Processing (NLP) and text analytics experts from pharmaceutical and biotech companies, healthcare providers and payers gathered together to discuss the latest industry trends and to hear the product news and case studies from Linguamatics on August 26th.

The keynote presentation from Dr Gabriel Escobar was the highlight of the event, covering a rehospitalization prediction project that the Kaiser Permanente Department of Research have been working on in collaboration with Linguamatics.

The predictive model has been developed using a cohort of approximately 400,000 patients and combine scores from structured clinical data with factors derived from unstructured data using I2E.

Key factors that could affect a patient’s likelihood of rehospitalization are trapped in text; these include ambulatory status, social support network and functional status. I2E queries enabled KP to extract these factors and use them to indicate the accuracy of the structured data’s predictive score.

Leading the use of I2E in healthcare, Linguamatics exemplified how cancer centers are working together to develop queries for pathology reports, mining medical literature and predicting pneumonia from radiology reports. They also demonstrated a prototype application to match patients to clinical trials and a cohort selection tool using semantic tagging of patient narratives in the Apache Solr search engine.


(Cambridge, UK & Boston, USA - 2 September 2014) - Today, Linguamatics I2E Semantic Enrichment has been selected as a KMWorld 2014 Trend-Setting Product.

I2E Semantic Enrichment, the newest offering from Linguamatics, is used within an existing enterprise search deployment to enrich the current search metadata to make information more discoverable and provide more relevant search results.

I2E Semantic Enrichment uses Linguamatics’ text analytics platform, I2E, to bring powerful semantic and natural language processing (NLP) technology to enterprise search applications, particularly within life sciences and healthcare.

The system scans millions of documents, to identify and mark-up semantic entities such as genes, drugs, diseases, organizations, authors, patient characteristics and lifestyle factors plus other relevant concepts and relationships.

Enterprise search engines consume this enriched metadata to provide a faster, more effective search for users. This results in a richer search experience, increased findability and improved speed to insight, enabling users to be more productive and spend less time on search.

 “I2E Semantic Enrichment was selected by the panel because it demonstrates innovative use of natural language processing-based text analytics to address the issue of enterprise search findability, bringing better search results to the most important stakeholder – the customer." says Hugh McKellar, KMWorld Editor-in-Chief.

Dr. Phil Hastings, SVP Sales and Marketing at Linguamatics comments “We’re honored to receive this recognition from KMWorld.