Development and application of techniques and algorithms to solve problems that are currently best solved by humans. Specifically, the group has experience in solving complex problems by taking advantage of machine learning, case-based reasoning, appropriate knowledge representation, the use of intelligent agents, as well as optimisation through evolutionary computation.
Extensive experience in the application of techniques and algorithms to solve problems requiring automatic knowledge discovery from large amounts of data, creating automatic prediction models and/or applying structuring or dimensionality reduction techniques.
Natural language processing:
Application of advanced semantic natural language processing techniques for spam filtering or automatic extraction of information from biomedical literature.
Development, application and fine-tuning of techniques for computer-based biological problem solving through the analysis of large amounts of experimental data (high throughput), including next generation sequencing or proteomics, as well as the integration of information from publicly available biological databases.
Clinical decision support systems:
Development of clinical decision support systems based on the use of artificial intelligence, machine learning and deep learning techniques for the exploitation of electronic medical records, including structured and unstructured information, as well as for the creation of CAD (Computer Aided Diagnosis) systems from medical images.