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Maven Semantic Healthcare Database (SME Package)
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Description: |
What is Maven:
- Largest database of international medical professionals, over 6,000,000 people and over 500,000 medical organisations;
- All records are downloadable to excel or inhouse database, with email, postal address and phone contacts;
- Profile and segment the entire database using over 47,000 diseases and therapeutic areas
What is Maven used for:
- Building prospect lists for postal, telesales and email campaigns
- Locating key decision makers in companies, hospitals, government labs, university labs, and other healthcare facilites
- Identifying candidates for recruitment to very specific life science positions
To try some test searches for yourself please click on www.mavensemantic.com
About the Maven Semantic Medical Database:
The current database holds over 6 million medical professionals, and 500,000 medical organisations.
The Maven Semantic medical database covers pharmaceutical, biotech and medical device companies, clinical research labs, hospitals, medical universities and government research organisations.
Maven is a SaaS subscription-based service. Clients can choose from quarterly or yearly subscriptions, or as pay-as-you-go option to retrieve specific large datasets for in-house use.
Results can be viewed online, or exported to Excel or a CRM system.
The data is now available to international healthcare marketing teams.
About our Technology: www.mavensemantic.com
Semantic data mining tools have been used to create a database of detailed profiles of life science companies and executives.
The system uses the open web as an underlying database and extracts specific information on people, job titles, biographies, research profiles, contact details (dept., phone, fax, and email), organisation profiles, websites, product/services and much more.
Maven is based on healthcare crawlers/bots, search technology, semantic parsers, clustering, natural language processing (NLP) and artificial intelligence (AI) technology.
"The system uses the context in which a given person appears, using artificial intelligence techniques to find out information not otherwise visible - for example, how important is this person in a specific medical research specialization," says Alejandro Mesas, Semantic Systems Architect. "The big advantage of a focused semantic healthcare database over a generic search engine is that it has built-in taxonomies and a thesaurus to expand and refine the user queries. We then use scoring and ranking to fine tune the relevance of the results for a given therapeutic area. For example, stem cell researchers are given a "page rank", based on where they work, their job title, how many times they have published, where they have published, etc. The relevance can be fine tuned by the user". |
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Maven Semantic Healthcare Database (SME Package)
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