Author Archives: Jose C. Gonzalez

About Jose C. Gonzalez

CEO at MeaningCloud. PhD in Telecommunication Engineering. Professor at Technical University of Madrid (1985-2015).

MeaningCloud Sponsors PharmaForce 2017

PharmaForce 2017

MeaningCloud sponsors PharmaForce 2017

At MeaningCloud, we are proud to sponsor the PharmaForce 2017 Conference. PharmaForce is an interactive conference for marketing and sales leaders from pharmaceutical companies to be held on September 18-20, 2017, in Austin, TX.

PharmaForce is the event for Pharma commercial innovators.

Who should attend:

  • Marketing:
    Consumer/HCP/Payer Marketing, Managed Markets, Marketing, Social Media Strategist, Commercial Marketing, Multichannel Marketing, Digital Marketing/Digital Strategy
  • Sales:
    Field Force/Sales Force Effectiveness, Sales Training & Development, Commercial/Sales Operations, Field/Regional/Account Manager, Market Access
  • Brand & Commercial Strategy:
    Commercial Innovation, Brand Management/Strategy, Brand Marketing, Disease, Drug, and Therapy Area Heads

Now in its 11th year, PharmaForce is the only life sciences event that addresses both marketing and sales strategies to achieve commercial success.

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Voice of the Patient Analysis in Forums

Voice of the Patient Analysis

In a previous post (Listening to the Voice of the Patient), we made an account of ongoing initiatives by public administration, hospitals and pharma companies intended to listen, understand and engage patients in the whole healthcare system. We also provided evidence that forums are a paramount source of information when talking about the Voice of the Patient Analysis.

As it was already shown, the Voice of the Patient (VoP) can be analyzed from multiple perspectives. In this post, we cover the point of view of the Pharma Industry.

Pharma Market Intelligence - Voice of the Patient

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MeaningCloud sponsors prize for Author Profiling Research

Author Profiling ResearchCLEF Initiative and Conference

MeaningCloud sponsors the prize to the best team at the 5th International Competition on Author Profiling Research, PAN@CLEF 2017. This competition is part of PAN (Plagiarism, Authorship and Social Software Misuse), a series of scientific events and shared tasks on digital text forensics. The 17th evaluation lab on digital text forensics will be held as part of the CLEF conference in Dublin, Ireland, on September 11-14, 2017.

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Listening to the Voice of the Patient

Voice of the Patient and Patient-Centered Health Care

National Library of Medicine

The modern definition of “patient centered health care” was stated in the National Library of Medicine’s MED-LINE subject heading (MeSH), introduced in 1995, which reads, “Design of patient care wherein institutional resources and personnel are organized around patients rather than around specialized departments.”

Following this design criterion, patients’ safety and well-being are the priority for all the agents involved in this industry: caregivers, pharmaceutical companies, medical device manufacturers, health insurers, and government agencies. And, being the center of our health systems, listening and engaging patients becomes the cornerstone of any quality improvement initiative. That’s why the so called “Voice of the Patient” is getting an increasing attention by all the stakeholders involved.

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Real World Evidence Definition

Real World Evidence Definition

Real World Evidence is information on health care that is derived from multiple sources outside typical clinical research settings, including electronic health records (EHRs), claims and billing data, product and disease registries, and data gathered through personal devices and health applications.

The most quoted definition of Real World Data comes from the area of pharmacoeconomics. The ISPOR (International Society for Pharmacoeconomics and Outcomes Research) defines Real World Data as:

“Data used for decision making that are not collected in conventional randomized controlled trials (RCTs)”

Other definitions of Real World Data, Real World Evidence and Evidence from Clinical Experience can be found in the following figure, taken from a working paper of the Margolis Center for Health Policy, Duke University (see References below).

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MeaningCloud Sponsors the Real World Evidence Forum 2017

Real World Evidence Forum

Real-World Evidence Forum

Real-World Evidence Forum Philadelphia, July 17-18

At MeaningCloud, we are proud to sponsor the Real World Evidence Forum. The RWE Forum, taking place on July 17-18, 2017 in Philadelphia, will bring together clinical health professionals to address:

  • How to operationalize the process of collecting real-world data.
  • How to utilize real-world evidence to demonstrate both the clinical effectiveness and cost-effectiveness of drugs.

Attendees will gain a better understanding of how electronic data sources are changing the way real-world data is being collected. This conference will offer attendees insight into how real-world evidence will help decrease costs, define innovative outcomes and minimize the number of patients exposed to potentially harmful medications.

Text Analytics and Real World Evidence

MeaningCloud, as a Text Analytics provider, has evolved a highly specialized offering for the Health and Pharma industries. We count among our clients some the largest companies in the Pharmaceutical industry.

Join us in Philadelphia. If you are interested in attending the Real World Evidence Forum next July 17-18, just drop us a line to info@meaningcloud.com. We have a surprise for you!

Stay tuned to access our presentation at the conference, that we will publish on this blog. In the meanwhile, if you are curious about how our technology works in the health area, just take a look at our Text Analytics Health Demo.

Looking forward to seeing you at the Real-World Evidence Forum!

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Language Technology Industry meets in Brussels, May 16-17, 2016

Language Technology Industry Summit

Logo_LTi_2016

LT-Innovate, the Language Technology Industry Association, organizes a new edition of its annual Summit. It is the yearly point of convergence between the Language Technology Industry, its clients, research partners and policy makers. According to its Memorandum of Association (London, 2012), LT-Innovate is a non-governmental organization consisting of all parties involved in the field of Language Technologies (LT) and services. Main goals are the promotion of common interests in the successful development, production, delivery and use of language technologies and services and the implementation of services that may help to promote the industry.

LTI Cloud

Besides traditional sections, as Solution Showcases, Technology Spotlights, and Project Results, Language Technology Industry Summit 2016 will serve as the official launch of one of the most important endeavours undertaken by the Association since its inception: the LTI Cloud.

LTI Cloud is the one-stop-shop platform for making available, discovering, assembling, testing and prototyping language technology components. If you are a potential provider of LT APIs (researcher, developer, startup…), and you want to get exposure, testing, or simply customers, consider using LTI Cloud, as it is a ready-to-use platform.

Still in a pilot phase until May 17th, you can be among the first adopters of LTI Cloud. And remember that it serves not only LT providers but also final users. Jochen Hummel, the leader of this initiative, will make the presentation at the Conference. By now, you can take a look at this preview.

Coming back to the Summit, I would like to stress a traditional track: “Customers challenge the Industry”. This year’s challenge comes from Elsevier: “Dynamic Knowledge Stores and Machine Translation”. It will be presented by Michelle Gregory and Pascal Coupet.

MeaningCloud User Profiling API

Being MeaningCloud one of the founding companies of LT-Innovate, we are proud to take an active role again in this year’s event. On Tuesday 17th of May, I will be presenting our recent work on “Automatic Extraction of Rich Customer Profiles from their Activity in Social Networks”. It is about our brand new MeaningCloud API for automatic profiling of Twitter users. User Profiling API allows extracting some important demographics according to different aspects for a given Twitter user: which topics the user talks about, personal and professional information, hobbies and interests, etc. This information extraction is based on a mixed rule-based and machine learning approaches.

Conference Discount Code

Come and join us at the LT-Innovate Summit. And, before registration, do not forget to ask for a special discount code through our helpdesk (support@meaningcloud.com).

Daedalus is now Sngular Meaning

[See the UPDATE section at the end of this post to know about the relationship between Sngular and MeaningCloud, as of June 1st, 2017.]

I am thrilled to announce that Daedalus, the company that I founded in 1998 in Spain, is now part of the Sngular group. This operation is part of a merger of five complementary IT companies to form a corporation based on talent and innovation, with the purpose of serving better our customers in times of accelerated changes.

As a consequence of this M&A operation, Daedalus has been renamed Sngular Meaning, raising series C funding from Sngular, its parent company, to accelerate its international development.

What does this deal mean for MeaningCloud?

Logo MeaningCloudMeaningCloud LLC is the branch of Sngular Meaning in the United States, in charge of development and marketing of our text analytics services. It is our strategic bid to consolidate as an international reference in the field of semantic technologies.

For MeaningCloud, this deal assures:

  • The financial resources for a faster expansion of our international business.
  • New marketing channels through cooperation with our Sngular sibling companies.
  • New opportunities to build specific solutions for vertical markets.

Some figures about MeaningCloud (that quickly become obsolete):

  • 5,000 registered users.
  • 1,000 active users in the last month.
  • 5 million API calls per day.

What is the structure of Sngular?

The companies that form the Sngular group are:

In total, we add up to a total of 300 people, with branches in the United States, Mexico and Spain. We define ourselves as a talent tech team. We will be visible under the domain sngular.team. Our CEO is Jose Luis Vallejo.

Regarding Sngular Meaning, besides the incorporation of Jose Luis Vallejo to the Board of Directors, there are no other changes at the management level. On my side, I will continue as President at Sngular Meaning and CEO at MeaningCloud. We can assure the continuity of our strategy around our trademarks MeaningCloud and Stilus.

When is the kick off?

On October 8th we will make a public presentation of the new Sngular group. This will be an event for employees and customers (by invitation only), but we plan other open events for later.

This is an exciting moment for us. We look at the future with confidence. I am sure that, as members of the Sngular family, we will continue enjoying the affection and support of all of you: customers, business partners and friends. Wish us luck and thank you for remaining at our side!

UPDATE as of June 1st, 2017

Almost two years later, anybody can see that the Sngular merger was a great success. What was founded as an umbrella corporation formed by five sister companies is now a strong IT company with multinational presence, where four of the original founding companies are fully merged. Besides this, other companies have been merged into Sngular through different mechanisms during the last months.

Regarding Sngular Meaning, we have jointly decided to integrate the service-oriented Data Science and Big Data activities in Sngular, while retaining all the activities and assets in the area of Text Analytics and Natural Language Processing in general. The Spain-based company Sngular Meaning (formerly Daedalus) has been renamed MeaningCloud Europe SL, owning 100% of the US-based company MeaningCloud LLC. Sngular maintains a non-controlling interest in our renewed and renamed company.

Long live Sngular! Long live MeaningCloud!

Jose C. Gonzalez

Emergency Management through Real-Time Analysis of Social Media

Serving citizens without paying attention to social media?

App Llamada Emergencias

The traditional access channels to the public emergency services (typically the phone number 112 in Europe) should be extended to the real-time analysis of social media (web 2.0 channels). This observation is the starting point of one of the lines which the Telefónica Group (a reference global provider of integrated systems for emergency management) has been working in, with a view to its integration in its SENECA platform.

Social dashboard for emergency management

At Daedalus (now MeaningCloud) we have been working for Telefónica in the development of a social dashboard that analyzes and organizes the information shared in social networks (Twitter, initially) before, during and after an incident of interest to emergency care services. From the functional point of view, this entails:

  • Collecting the interactions (tweets) related to incidents in a given geographical area
  • Classifying them according to the type of incident (gatherings, accidents, natural disasters…)
  • Identifying the phase in the life cycle of the incident (alert or pre-incident, incident or post-incident)

Benefits for organizations that manage emergencies

Love Parade Duisburg

Love Parade Duisburg

Anticipate incidents

Anticipation of events which, due to their unpredictability or unknown magnitude, should be object of further attention by the emergency services. Within this scenario are the events involving gatherings of people which are called, spread or simply commented through social networks (attendance to leisure or sport events, demonstrations, etc.). Predicting the dimensions and scope of these events is fundamental for planning the operations of different authorities. We recall in this respect the case of the disorders resulting from a birthday party called on Facebook in the Dutch town of Haren in 2012 or the tragedy of the Love Parade in Duisburg.

Flood in Elizondo, Navarre, 2014

Flood in Elizondo, Navarre, 2014

Enrich the available information

Social networks enable the instant sharing of images and videos that are often sources of information of the utmost importance to know the conditions of an emergency scenario before the arrival of the assistance services. User-generated contents can be incorporated to an incident’s record in real time, in order to help clarify its magnitude, the exact location or an unknown perspective of the event.

 

 

Text Analytics technology

Logo MeaningCloud

For the analysis of social content, the text analytics semantic technology (text mining) of MeaningCloud is employed. Its cloud services are used to:

  • Identify the language of the message
  • Classify the message according to a taxonomy (ontology) developed for this scenario (accidents of various kinds, assaults, natural disasters, gatherings, etc.)
  • Extract the mentioned entities (names of people, organizations, places) and the message’s relevant concepts
  • Identify the author or transmitter of each tweet.
  • Extract the geographic location of the transmitter and the incident
  • Extract the time of the message and the incident
  • Classify the impact of the message
  • Extract audiovisual (pictures and videos) and reference (links to web pages, attached documents…) material mentioned in the tweet for documenting the incident
  • Group automatically the messages relating to a same incident within an open record
  • Extract tag clouds related to incidents

Twalert Console

Twalert ConsoleA multidimensional social perspective

Text analytics components are integrated into a web application that constitutes a complete social dashboard offering three perspectives:

  • Geographical perspective, with maps showing the location of the messages’ transmitters, with the possibility of zooming on specific areas.
  • Temporal perspective: a timeline with the evolution of the impact of an incident on social networks, incorporating sentiment analysis.
  • Record perspective: gathering all the information about an incident.

Twitter Accidente Trafico

LT-Accelerate

Telefónica and Daedalus (now MeaningCloud) at LT-Accelerate

Telefónica and Daedalus (now MeaningCloud) will jointly present these solutions at the LT-Accelerate conference (organized by LT-Innovate and Seth Grimes), which will be held in Brussels, on December 4 and 5, 2014. We invite you to join us and visit our stand as sponsor of this event. We will tell you how we use language processing technologies for the benefit of our customers in this and other industries.

 

Register at LT-Accelerate. It is the ideal forum in Europe for the users and customers (current or potential) of text analysis technologies.

Telefonica_logo

 

 

 

 

 

Jose C. Gonzalez (@jc_gonzalez)

[Translation from Spanish by Luca de Filippis]

The Role of Text Mining in the Insurance Industry

What can insurance companies do to exploit all their unstructured information?

A typical big data scenario

Insurance companies collect huge volumes of text on a daily basis and through multiple channels (their agents, customer care centers, emails, social networks, web in general). The information collected includes policies, expert and health reports, claims and complaints, results of surveys, relevant interactions between customers and no-customers in social networks, etc. It is impossible to handle, classify, interpret or extract the essential information from all that material.

The Insurance Industry is among the ones that most can benefit from the application of technologies for the intelligent analysis of free text (known as Text Analytics, Text Mining or Natural Language Processing).

Insurance companies have to cope also with the challenge of combining the results of the analysis of these textual contents with structured data (stored in conventional databases) to improve decision-making. In this sense, industry analysts consider essential the use of multiple technologies based on Artificial Intelligence (intelligent systems), Machine Learning (data mining) and Natural Language Processing (both statistical and symbolic or semantic).

Most promising areas of text analytics in the Insurance Sector

Fraud detection

Detección de Fraude

According to Accenture, in a report released in 2013, it is estimated that in Europe insurance companies lose between 8,000 and 12,000 million euros per year due to fraudulent claims, with an increasing trend. Additionally, the industry estimates that between 5% and 10% of the compensations paid by the companies in the previous year were due to fraudulent reasons, which could not be detected due to the lack of predictive analytic tools.

According to the specialized publication “Health Data Management”, Medicare’s fraud prevention system in the United States, which is based on predictive algorithms that analyze patterns in the providers’ billing, in 2013 saved more than 200 million dollars in rejected payments.

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