Projects: e-Health

ANESTECH is a project of the Instituto de Biomecánica (IBV), supported by the Agencia Valenciana de la Innovación (AVI), which develops a remote pre-anaesthetic assessment methodology based on artificial intelligence. The system allows patients to record videos of their face and neck from their smartphone, which are then analysed using 3D reconstruction and AI algorithms to assess the airway and estimate the anaesthetic risk. The platform is integrated into a secure digital environment connected to the Electronic Health Record. ANESTECH improves hospital efficiency, reduces travel and promotes a more accessible and patient-centred healthcare model.

High-value care education

Digital medical devices for healthcare transformation

Leveraging health data for innovation

EducaTH studies healthy lifestyles after liver transplants. Among various multidisciplinary studies carried out by La Fe, SABIEN is developing a mobile app that allows patients to monitor their own progress, receive advice and collect data.

Design and development of a mobile application prototype that allows non-professional caregivers of patients to find volunteers who can temporarily relieve them so they can carry out essential personal activities such as shopping, or simply rest, with the consequent impact on health. The application will facilitate coordination between caregivers and volunteers, as well as with case managers, improving the quality of life for caregivers and patients.

The PATRON-CGM project, developed by the UPV and FISABIO, aims to improve diabetes treatment through an artificial intelligence-based decision support system. It will analyse data from continuous glucose monitors (CGM) to identify patterns and optimise therapeutic adjustment, reducing errors and improving clinical efficiency. With this system, it is hoped to facilitate the integration of CGM in Type 2 diabetes and improve glycaemic control in patients.

The PREVILI project, led by the UPV, aims to prevent ventilator-induced lung injury (VILI) in neonatal and paediatric patients. Through the analysis of mechanical biomarkers and artificial intelligence models, the aim is to optimise ventilation to reduce respiratory complications and improve safety in ICUs. With this study, it is hoped to minimise mortality and improve the quality of life of the most vulnerable patients.

The future of health data management: Trends and new models for data platforms

Winning Users with Human-Centered Design