Cornell University: New Technique Boosts Online Medical Search Results
From Cornell University:
When looking for medical information on the internet, having the precise terminology makes the search fairly straightforward.
But what if the person doing the searching doesn’t know the exact terminology, or wants to see what other information may be available without using technical terms? Will internet queries yield any useful results – or worse, will they produce incomplete or downright incorrect information?
A Cornell-led group of researchers has developed a search method
“If the traditional way of searching for information is by using those official names or concepts, then it will lead to some bias in identifying the content because many people on the internet aren’t familiar with official medical vocabularies,” said Chau Tong, a postdoctoral associate in the Department of Communication, in the College of Agriculture and Life Sciences.
Tong is lead author of “Search Term Identification Methods for Computational Health Communication: Word Embedding and Network Approach for Health Content on YouTube,” which published Aug. 30 in the open-access journal JMIR Medical Informatics.
that employs natural language processing and network analysis to identify terms that are semantically similar to those for cancer screening tests, but in colloquial language.
About Gary Price
Gary Price (email@example.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.