Although many other researchers have been active in leveraging NLP for Medical researches, it seems that what is needed here is not coming up with particularly new algorithms, but utilizing existing text crawling methods to sum up and find related medical research results. Every year, or even every month, new research results come out, some confirming the previous findings, some contradicting with the previous research findings. It’s extremely hard for the med researchers to go through every articles which have been published which are relevant to their current research topics. This can result in redundant researches which cause waste of time, money and efforts of both the patients and medical experts. Although Pub Med and other meidcal websites, or even including Google Scholars and Mendeley seems to provide functions such as related papers or related topics, it might be useful for the programmers to develop a program or medical search engine which can compare and contrast highly relevant researches based upon the online documents.
Even advanced settings might assist the med experts to search results written in different languages, although it’s also true that most of the med professionals thesedays produce their research papers in English than any other languages.
With the similar but slightly different motives, NLP mgiht help legal experts across the countries to collaborate more efficiently by adopting NLP for their legal research, even with the presence of WestLaw and other online legal repositories.