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Semantic Computing in Healthcare

By   /  May 4, 2016  /  No Comments

Massive Wall of Organized Documentsby Angela Guess

Jennifer Bresnick recently wrote in Health IT Analytics, “Semantic computing relies on the notion that computers can be “taught” to approach concepts and problems in a similar way to humans.  By linking together certain natural language concepts instead of just solving mathematical equations, computers can make inferences about data sets that might not be hard-coded into the system from the start. Semantic analytics requires curators and data scientists to write algorithms that group carefully developed categories of data elements, such as patient names, diagnoses, locations, or economic statuses, into possible relationships, instead of creating a new equation involving specific data elements each time there’s a new question to ask.”

For example, a provider may have a list of patients in a traditional relational database that includes Joan Smith and Maria Smith.  That is very handy when Joan and Maria come in for their yearly physicals, but not so meaningful when Joan wants to talk about her family history of breast cancer or heart disease. That’s because the sentence ‘Maria is Joan’s sister’ requires a semantic understanding of key terms.  ‘Sister’ implies a relationship between three data elements: ‘Joan,’ ‘Maria,’ and the hidden, shared link that is ‘Joan and Maria’s mother’.”

Bresnick goes on, “Population health management and clinical decision support are all about relationships, too. The relationships between a patient and her environment, or a medication and an allergy, require computers to understand how one category of data elements impacts another to produce a result. As providers become increasingly responsible for everything that happens to a particular patient across multiple care settings, having a good grasp of the full scope of these relationships is becoming critical for reimbursement and better outcomes.”

Read more here.

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