A new series of videos has launched, showcasing partners from the DRAGON project. Each videos introduces you to a project partner and provides an overview of their contribution to the project. New videos will be posted to this page once released.

Navigating the sea of information surrounding COVID-19, data sharing in healthcare, and digital tools can be overwhelming for people seeking reliable guidance. Thanks to ELF, we have tackled this challenge head-on. In a collaborative effort, that included people with lung conditions, lung disease experts, and data specialists, DRAGON has able to offer informative and accessible resources. These resources offer an accurate and comprehensive understanding of critical topics, helping you make informed decisions about your healthcare journey.

Explore our ELF resources and gain valuable insights into the world of healthcare data, COVID-19, and digital tools. Empower yourself with knowledge and trust in the information you receive. You can access these invaluable resources by visiting the resources section. 

In the face of COVID-19 and potential future pandemics, we needed a solution that empowers patients, aids healthcare professionals, and accelerates research efforts. Enter the Comunicare App, developed with the collaboration of patients and healthcare providers.

For Patients and Citizens:
Comunicare enables individuals to access personalised information and self-management functionalities, putting them in control of their healthcare journey. With this app, patients become active participants in their health journey.

For Healthcare Professionals:
A follow-up dashboard for caregivers that provides data and analytics based on patient-reported outcomes. The platform is envisioned to integrate in the future a multifactorial decision support system, facilitating the analysis of various data types.

For Researchers:
Comunicare aims to streamlines COVID-19 research studies through trial Patient Decision Aids, a patented-pending solution enabling patients to inform themselves about relevant clinical studies, compare them whenever needed with the standard of care and capture their preferences for a well-informed decision. The objective is for researchers to be able to conduct more efficient and accessible research, ultimately contributing to a better understanding of the virus and potential future pandemics.

At DRAGON, we’re dedicated to strengthening the global response capacity of healthcare systems to combat COVID-19 and future pandemics.

CDISC, a dedicated partner in establishing clinical data standards, has developed an innovative tool that streamlines and harmonizes data from diverse clinical centers into one consistent structure. This approach aligns perfectly with the principles of federated learning by standardizing disparate data sources so that leading-edge Artificial Intelligence (AI) tools can access data from various locations without the need to have the data in one data source or database.

With this progressive tool, researchers can query and analyze data across multiple settings, essentially creating a virtual integration. This standardized data structure promotes comparability and facilitates large-scale data pooling, significantly enhancing the ease of data reuse and enabling exploration of more profound research questions using AI.

CDISC goes the extra mile to ensure the accurate and consistent implementation of their standard data structure that can easily be extended to cover additional biomedical concepts as required by different areas of research. They offer a wealth of resources, including guides, mappings, supplements, and educational materials, all designed to support researchers in leveraging this forward thinking tool, reducing challenges associated with transforming data into a single usable standard.

Imperial College London (YangLab) and the University of Cambridge (CMIH) have collaborated to pioneer ground-breaking data harmonisation techniques aimed at enhancing the quality and applicability of medical images, specifically tailored for CT, chest X-ray and radiomics analysis. Their joint effort has resulted in the creation of a sophisticated model designed to optimise image data for CT and chest X-ray scans in COVID-19 patients across various centres and scanners.

This achievement is the culmination of a rigorous and iterative process, guided by consensus clinical protocol guidelines for image capture, ensuring the highest level of precision. The final product of this meticulous work holds the promise of delivering significantly more accurate quantitative imaging biomarkers for COVID-19 patients, thereby enhancing diagnostic and treatment capabilities. Furthermore, the incorporation of harmonised non-imaging clinical data into the federated learning system represents a pivotal advancement, enabling a more comprehensive analysis of patient information. Anticipate the future of multimodal medical data analysis, as these cutting-edge developments are poised to revolutionise the way we approach personalised healthcare.

In the world of healthcare, managing patient data is a complex task. The DRAGON project, like many others, face the challenges of data silos and privacy barriers. That’s where Radiomics.bio steps in with DistriM – an innovative solution that prioritizes patient data privacy. Incorporating a federated approach, DistriM keeps data secure by staying within each clinical center. The data is standardized and anonymized, without ever leaving its source. AI models are then sent to these secure machines for training, enhancing accuracy without compromising privacy. This approach not only ensures data security but also minimizes legal and administrative hurdles, offering a streamlined solution for managing patient data. DRAGON is committed to safeguarding patient privacy and revolutionizing data management.