Strategic Research Control Engineering and Intelligent Systems (eXIT)

Control Engineering and Intelligent Systems (eXIT)

The eXiT-Health research group focus the advances of Artificial Intelligence and Machine Learning Techniques in the field of Medicine and Healthcare.

Technical expertise includes:

  • Multivariate Statistical Process Control:  Strategies for large number of variables, dimensionality reduction.
  • Case Based Reasoning: Individual, personalized decision making, similarity measures, attribute learning.
  • Machine learning: Structured data mining (sequence pattern mining), boosting, genetic algorithms, SVM, big data (data analysis)
  • Qualitative representation of trends: Numeric to qualitative representations, signals as sequences of episodes.
  • Optimization: Heuristic and meta-heuristics methods (Simulated Annealing, Genetic Algorithms, Swarm-based methods)

Applied expertise in Medicine and Healthcare contains:

  • Personalized diabetes prediction based on phenotypes
  • Hereditary information management for breast cancer prognosis
  • Clinical workflow support for Transcatheter Aortic Valve Implantation
  • Patient empowerment: Premature babies monitoring at home
  • Sensor data analysis to predict rehabilitation duration

Main projects

  • 1.

    PEPPER – Patient Empowerment through Predictive PERsonalised decision support.

    The project seeks to develop a personalised decision support system for chronic disease management. The system, which combines case-based reasoning with predictive computer modelling, will empower patients to self-manage their diseases such as diabetes. Ref. H2020 PHC-28-2015, GA 689810.

  • 2.

    MoSHCA – My Mobile and Smart Health Care Assistant

    The main objective of MoSHCA is to develop intelligent healthcare system solutions for patients with chronic diseases(diabetes, epilepsy, pregnancy related disorders, etc ) and general health monitoring (baby monitoring and general health) through medical sensors and smartphones. The eXiT group is in charge of novel intelligent algorithms, decision making models and alerts for premature baby monitoring at home, and heap surgery rehabilitation. Ref. EUREKA ITEA 2 nº 11027 – IPT-2012-0943-300000.

  • 3.

    MEDIATE - Patient Friendly Medical Intervention

    The objective of the Mediate project is to increase productivity and effectiveness in healthcare and reduce patient risk and discomfort by supporting healthcare professionals in the transition from invasive, open surgery to minimally invasive, image guided intervention and treatment (IGIT). By empowering the healthcare professional through more advanced technologies during the whole treatment cycle, IGIT helps them to obtain a better clinical outcome of the treatment, predictable procedure times, fewer complications, better service to the patient and lower morbidity & mortality rates. The eXiT has developed a Clinical Decision Support System based on Case-Based Reasoning to support decision making in Transcatheter Aortic Valve Implantation Intervention. This project has received the ITEA Excellence Awards 2015. Ref. Eureka ITEA 2 no 09039 - TSI-020400-2010-84.



Bioinformatics expertise:

Group Leader:

Beatriz López

Bioinformatics services offered