Category Archives: Text Analytics

Post that discuss text analytics technology.

Our experience on Adverse Drug Reactions (ADR) identification at TAC2017

MeaningCloud and LaBDA research group were present at the TAC 2017 conference held on November 13th – 14th at NIST headquarters in Washington. In the Text Analysis Conferences, research groups from all over the world were invited to develop software systems to tackle text analytics-related problems. This year, one task was devoted to the automatic identification of adverse drug reactions (ADRs) appearing in drug labels, including features defining the ADR, such as its severity or if it is characteristic of a drug class instead of just a given drug. There has been a specific subtask to link the identified ADRs with their corresponding MedDRA codes and lexical terms. More than 10 research teams have taken part in the project, all of them applying some kind of deep learning approach to the problem. Results show that it is possible to reach 85% accuracy when identifying ADRs.

We were delighted to present our text analytics-based system for ADRs identification on drug labels, which combines natural language processing and machine learning algorithms. The system has been built as a joint effort between MeaningCloud and LaBDA research group at the Universidad Carlos III de Madrid. Identifying ADRs is a basic task for pharmacovigilance, and that is the reason why the Federal Drug Administration (FDA) is involved in the funding and definition of the ADRs identification tasks in the framework of the Text Analysis Conferences. We have learned a lot these days (e.g., a BiLSTM deep neural network is the best choice for the purpose), and shared pleasant moments with our colleagues at Washington. We hope to be able to attend next year’s edition, which will focus on the extraction of drug-drug interactions (DDI), another interesting task aimed at detecting situations where the use of a combination of drugs may lead to an adverse effect.


MeaningCloud’s Artificial Intelligence at EyeforPharma

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Text-based Artificial Intelligence for the Pharma Industry

At MeaningCloud, we are proud to sponsor the Eye for Pharma Conference. Data, Evidence and Access Summit 2017. November 13-14th, 2017 – Philadelphia, US. MeaningCloud’s value proposition for the conference can be summarized as Text-Based Information with Artificial Intelligence.

Eye for Pharma is about demonstrating and communicating value, no matter which department you’re in. Whether it’s exploring innovative uses of real-world evidence (RWE) or creating new outcomes-based pricing models, only by embracing the power of data can you fully unlock the value of your drugs. It is a great opportunity for learning and networking.

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Surveys and HR: why do you need open-ended questions?

open and closed questions

Since everyone wants to understand employees better, text-based data sources are a key factor for any organization to understand the “whys” and act on them to make improvements. Open-ended questions are one of the most effective ways to gather employee opinions; they offer them an open forum to make suggestions and present innovative ideas.

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The amazing deeds of text analytics superheroes

In the last few years, the explosion of user-generated content in social media (networks, forums, communities, etc.) has significantly increased the need to extract information from unstructured content. Oddly enough, text analytics superheroes, wondrous as their achievements are, are just average guys who figured out what they could do with the right technology.

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What is the Voice of the Employee (VoE)?

Voice of the Employee. Silhouettes with bubbles representing dialog

Finding committed employees is one of public and private organizations’ top priorities. Thus, listening to the Voice of the Employee by systematically collecting, managing and acting on the employee feedback on a variety of valuable topics is essential.

The relationship between Voice of the Employee (VoE) and Engagement is very similar to the one between Voice of the Customer (VoC) and Customer Experience. VoC provides information to improve customer experience. Voice of the Employee promotes employees’ engagement in the company and their work. See: Voice of the Employee, Voice of Customer and NPS

Voice of the Employee collects the needs, wishes, hopes, and preferences of the employees of a given company. VoE considers specific needs, such as salaries, career, health, and retirement, as well as implicit requirements to satisfy the employee and gain the respect of colleagues and managers.
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Text Analytics & MeaningCloud 101

One of the questions we get most often at our helpdesk is how to apply the text analytics functionalities that MeaningCloud provides to specific scenarios.

Users know they want to incorporate text analytics into their processes but are not sure how to translate their business requirements into something they can integrate into their pipeline.

If you add the fact that each provider has a different name for the products they offer to carry out specific text analytics tasks, it becomes difficult not just to get started, but even to know exactly what you need for your scenario.

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In this post, we are going to explain what our different products are used for, the NLP (Natural Language Processing) tasks they are tied to, the added value they provide, and the requirements they fulfill.

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Voice of the Customer in the insurance industry

For insurance companies, it is vital to listen and understand the feedback that their current and potential customers express through all kinds of channels and touch points. All this valuable information is known as the Voice of the Customer.  By the way, we had already dedicated a blog post to Text mining in the Insurance industry.

(This post is a based upon the presentation given by Meaning Cloud at the First Congress of Big Data in the Spanish Insurance Industry organized by ICEA. We have embedded our PPT below).  

More and more insurance companies have come to realize that, as achieving product differentiation at the industry is not easy at all, succeeding takes getting satisfied customers.

Listening, understanding and acting on what customers are telling us about their experience with our company is directly related to improving the user experience and, as a result, the profitability. In the post on Voice of the Customer and NPS, we saw in more detail this correlation between customer experience and benefits.

 

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