Natural Language Processing: Standing on the shoulders of giants
Many of us know the joys and sorrows of research. Weeks, months and years can pass, developing hypotheses, working in the lab or clinic, analyzing results, sometimes going back to square one, but then writing the paper, and finally, seeing the final version published and in print. The intent is that your research is shared, discussed, re-used, so that others can build on it, “standing on the shoulders of giants,” as Isaac Newton famously said.
Traditionally, getting information out of written papers for re-use has been manual; individuals reading, reviewing and extracting the key facts from tens or hundreds of papers by hand, in order to summarize the most up to date research in a field, or understand the landscape of information around a particular research topic. Over the past few decades Artificial Intelligence (AI) tools, such as Natural Language Processing (NLP), have evolved that can hugely speed up and improve this data extraction. NLP solutions can enable researchers to access information from huge volumes of scientific abstracts and literature; developing strategies and rules that drill deep into literature for hidden nuggets, or more broadly, ploughing the landscape for the nuggets of desired information.
To give you a couple of examples, I’ll share two use cases, both published recently, that use Linguamatics NLP platform across published literature, enabling researches to benefit from years of previous research.