Multidisciplinary project involving natural language processing and machine learning for clinical language processing

The focus is on proposing to automatically discover similarities among different morbidities that could lead to candidate illnesses for joint treatment. To go beyond combinations of diseases that may be well known in the clinical literature, this proposal aims to exhaustively compare similarities between diseases at a large scale to identify possible candidate combinations. This involves extracting relevant information about diseases from sources including medical taxonomies and encyclopedias and creating a representation for each of the conditions and their properties that allows for their comparison. In addition, techniques for identifying similarities between representations will be used for large-scale comparison of diseases according to their common characteristics, including symptoms, treatments and evolution. These will enable the discovery of candidate combinations of diseases that have similar characteristics and could have joint treatments.