In recent years the volume of information available electronically has increased exponentially, coining the term Big Data to refer to this
phenomenon. The medical domain is an area in which the number of documents generated by the centers for patient primary care constantly increases. However, a bottleneck is generated because processing these documents requires specialized personnel craftly performing tasks. In this framework, the development of automated tools of textual analysis can be a breakthrough for health systems. This project will develop a set of processors that allow automatic analysis of medical texts taking into account criteria of robustness, high precision and coverage. Computer technologies have reached a level of maturity where it is possible to have tools that can help medical staff to increase productivity.
This project will result in a set of tools that, using advanced methods and algorithms, will provide a comprehensive and versatile tool set for the following tasks:
- Morphological, syntactic and semantic analysis of medical texts according to the state of art in natural language processing. An important point is to go beyond the generic linguistic processors and adapt them to the medical domain, especially in recognition of named entities, which are especially important in the treatment of medical texts, such as drugs, chemicals, diseases, symptoms, procedures or body parts.