The CLARIFY Decision Support Platform (DSP) is a responsive web application designed to support decision-making in cancer care through real-time data integration and predictive analytics. Built on Big Data Europe, the platform integrates a variety of data, including scientific publications, clinical anonymized data from EHR, genomic data, wearable monitoring data, and quality of life questionnaires. […]

Currently, the practice of recording clinical information in “free text” offers flexibility, but hinders automatic data extraction, limiting the application of analytical models. Most records are unstructured, and the use of non-standard abbreviations increases ambiguity, making interpretation difficult. Manual review is slow and prone to errors, while clinical decision support systems, which rely on structured

The goal of the FAITH project (Federated Artificial Intelligence solution for moniToring mental Health status after cancer treatment) is to remotely identify and predict depressive symptoms in cancer survivors using a federated machine learning approach that prioritizes privacy. The target audience includes healthcare professionals, researchers, technology developers and cancer survivors. The FAITH project leverages the

The Elderly Care Ecosystem (ECE) is an integration of various digital health technologies, exploring the areas of telehealth and predictive analytics. The goal of this ecosystem is to improve the quality of life for elderly individuals by providing tailored care services that adapt to their changing needs over time, promoting greater autonomy and well-being. With

The SCAARF technology aims to offer an alternative method to alleviate anxiety symptoms in a non-intrusive and subconscious way. This technology is an innovative idea in the field of digital health and wearable technology, designed for people who suffer from anxiety disorders. SCAARF technology consists of a smart scarf that incorporates a sensor that detects

Nearly half of all adults in the United States have hypertension, one of the leading risk factors for cardiovascular disease, and only about a quarter (24%) of those people have their hypertension under control. Studies show that there are racial, ethnic, and socioeconomic disparities in the awareness and treatment of hypertension. Patients from groups traditionally

IPDM has significant potential to improve diabetes management and drive health system reforms to become high-performing, effective, equitable, accessible, and sustainable. Evidence and good practices inspire health system transformation. Adopting person-centred approaches like co-creation and shared decision making enhances patient engagement and outcomes. Technological advances, including AI, are foreseen to improve diabetes care through automation