Swanson's Model for Biomedical Discoveries:

Text-mining of scientific literature available today is a difficult task. Many text
mining algorithms have been developed in recent years. But, there are some
limitations to these techniques such as speed and many of these algorithms are
not available in open source. In order to be updated, the researchers need to use
automated text-mining tools. Also, with so much of literature available in the
biomedical field, it is impossible to manually go through these texts. So, with
the help of computer algorithms and artificial intelligence techniques, we can
actually discover new things by correlating the already existing biomedical
literature. To support the experts in the field of Biology and Medicine, I have
developed a text-mining method which outputs sentences that can be read by
experts to develop relations between biomedical concepts in a given set of
abstracts. The method that I have implemented is based on the Swanson’s ABC
Model for Biomedical Discovery. The program searches for rare terms in the
abstracts. These rare terms indicate a relation that has not yet been established. I
have used functions (programmed in R language) on Vitiligo disease dataset as a
source of data. With the help of experts, new relations might be discovered and
this can help in better understanding of Vitiligo disease.