Healthcare has been moving to online services for quite some time now. The portals allow users to seek solutions to their health problems and find resources in choosing doctors. There are also more alternative resources that deal with cures, home remedies, and a natural approach to health care.
All of this information is considered valuable and recently ‘dMetrics’ of Massachusetts Institute of Technology (MIT) agreed. The information given by online users can potentially be used to perform research and develop new products. This interesting information came to us from Crazy Engineers and their article, “Software To Study Online Chatter For Predicting Healthcare Consumers’ Behaviour.”
The health care industry recognizes these large chunks of unstructured data could be put to use to extract useful information. ‘dMetrics developed a platform known as ‘DecisionEngine’ which is based on machine learning and natural language processing techniques.
It helps computers to understand human language efficiently and process the available conversations, regarding drugs, medical devices, and other health care products. DecisionEngine sorts out the useful data and processes it.
In lieu of an ontology, they have devised ‘DecisionEngine’ in such a way that it can extract the information from slangs, misspellings, run-on sentences, and crazy use of punctuation. It has an algorithm consisting of 2 million lines of code, which when combined can became powerful enough to comprehend spoken human language.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.
