Liss Hernández


Liss is Automatic Engineer, by the José Antonio Echeverría Technological University of Havana, with a Master of Telemedicine and Bioengineering, by the Technical University of Madrid. She is a researcher at Life Supporting Technologies (LifeSTech) research group and has collaborated in several R&I projects in the area of e-Health applied to diabetes disease management and identifying risk factors influencing uptake and progression of diabetes as part of the MOSAIC project (FP7-ICT-2011.5.2-600914).
She also participated in European funded project BD2Decide (H2020-689715), the aims to develop a more precise prognostic prediction in Cancers of Head and Neck region (H&NC), in order to maximize the therapeutic results and minimize the impacts of HNC therapy by applying Big Data techniques. She led the technological work in the MiniQ project of EIT-Health initiative that aims at optimizing drug treatment among older people through a patient-centred, web-based decision support system.
Currently, she is involved in innovative European projects focused on the improvement of the Quality of Life of oncology patients: BD4QoL (H2020-875192) and CAPABLE (H2020- 875052). In BD4QoL she works towards the improvement of HNC survivor’s Quality of Life through person-centred monitoring and follow-up planning by the contribution of artificial intelligence and big data and in CAPABLE by combining the most advanced technologies for data and knowledge management with a sound socio-psychological approach in order to develop a coaching system for improving the quality of life of cancer patients (kidney cancer and melanoma).
In addition, she leads the semantic work of the SuPerTreat-EraPerMed (Supporting Personalized Treatment Decisions in Head and Neck Cancer through Big Data) project and WeldGalaxy (H2020-822106) European project: a B2B online platform that brings together global buyers and sellers of welding equipment along with consumables and services.
She is expert in design, development and validation of platforms for monitoring and manages of chronic disease patients, in clinical data management systems, knowledge management systems and semantic technologies.

Current projects: BD4QoL (H2020-875192), SuPerTreat-EraPerMed, CAPABLE (H2020- 875052), WeldGalaxy (H2020-822106)


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