Deep learning applied to NLP has allowed practitioners understand their data less, in exchange for more labeled data. Thus, labeled data has become the bottleneck and cost center of many NLP efforts.
In this post we’ll discuss the recent paper TextRay: Mining Clinical Reports to Gain a Broad Understanding of Chest X-rays focusing on the best practices the paper exemplifies with regards to labeling text data for NLP.
What is TextRay ?
On Thursday June 7th 2018 a new customer emailed us reporting that they were unable to submit the work they’d done on our platform. The cause of this error was the deployment of an outdated version of our frontend. Other customer sites and customers who use our on-premise offering were not affected.
Labeled data has become paramount to the success of many business ventures and research projects. But obtaining labeled data remains a costly exercise. Active Learning is a technique that promises to make obtaining labeled data more efficient and has recently been hyped by a number of companies.