Extraction of Disease-Treatment in Short Texts

Machine Learning (ML) field of research is almost in many domains, and recently it becomes a powerful and reliable tool in the medical domain. ML is also being used for data analysis, such as detection of regularities from imperfect data. This project proposes a medical care application that is capable identifying and disseminating healthcare information. It extracts sentences from published medical papers that mention diseases and treatments, and identifies semantic relations that exist between diseases and treatments in short text. We also focus on three relations: Cure, Prevent, and Side Effect of a particular disease. Automatic Information Mapping provides the ease way of finding the relevant data among a pool of data.