Mining Unstructured Texts for Insights using Convolutional Neural Networks
Pharmaceutical and Healthcare domains deal with a tremendous amount of unstructured texts, which can be mined effectively using CNN for NLP approach. Malaikannan Sankarasubbu talk about these advanced techniques that can have many applications, such as, building better cohort for clinical trials or establishing better inclusion/exclusion criteria, among other uses.
Natural Language Processing, or NLP, has improved a lot in the past couple of years. We see lot of applications being built with NLP that weren’t possible before. Virtual Assistants, smart replies in email, text summarization, sentiment analysis, PHI Scrubber, Machine Translation, etc., are some examples of NLP applications. The healthcare industry generates a lot of unstructured text, such as, doctor notes. There are a lot of key insights that can be derived, if there is a way to apply NLP effectively to these unstructured texts.