Periodic Reporting for period 3 - DRAGON (The RapiD and SecuRe AI enhAnced DiaGnosis, Precision Medicine and Patient EmpOwerment Centered Decision Support System for Coronavirus PaNdemics)
Reporting period: 2022-10-01 to 2024-03-31
COVID-19 hit the world hard. It impacted on everyone’s lives and overwhelmed healthcare resources worldwide, which lead to deaths that could have been prevented. On the individual level, it was difficult for people to know what was happening, how to prepare and behave, when to seek medical help and what to do post-COVID-19.
DRAGON is an Innovative Medicines Initiative (IMI) project which started on 1 October 2020, in the middle of the 2nd wave of the COVID-19 pandemic, and ran for 3 years. The project was coordinated by the University of Maastricht with Radiomics as the Project Lead. The partners include high-tech, small and medium sized enterprises, academic research institutes, biotechnology partners , together with the patient centered organization, European Lung Foundation (ELF) and professional society, European Respiratory Society (ERS).
DRAGON is built on the ambition to increase the capacity of health systems, speed up the pace of research and innovation, and empower citizens during a pandemic if we:
• improve how we diagnose people
• are able to predict patient outcomes early on
• empower citizens and patients to participate in their diagnosis as well as care and research
DRAGON uses advanced approaches such as:
• artificial intelligence (AI) – algorithms that learn and improve when they are provided with new information
• patient and doctor decision support tools in the form of personal health applications (apps)
• molecular profiling (a way of classifying a condition or disease outcome based of its genetic and other biomarkers)
These approaches will help to increase healthcare capacity and enable the research and innovation process by making them more efficient and provide patients and the public with tools to help and guide them during a pandemic.
DRAGON is an Innovative Medicines Initiative (IMI) project which started on 1 October 2020, in the middle of the 2nd wave of the COVID-19 pandemic, and ran for 3 years. The project was coordinated by the University of Maastricht with Radiomics as the Project Lead. The partners include high-tech, small and medium sized enterprises, academic research institutes, biotechnology partners , together with the patient centered organization, European Lung Foundation (ELF) and professional society, European Respiratory Society (ERS).
DRAGON is built on the ambition to increase the capacity of health systems, speed up the pace of research and innovation, and empower citizens during a pandemic if we:
• improve how we diagnose people
• are able to predict patient outcomes early on
• empower citizens and patients to participate in their diagnosis as well as care and research
DRAGON uses advanced approaches such as:
• artificial intelligence (AI) – algorithms that learn and improve when they are provided with new information
• patient and doctor decision support tools in the form of personal health applications (apps)
• molecular profiling (a way of classifying a condition or disease outcome based of its genetic and other biomarkers)
These approaches will help to increase healthcare capacity and enable the research and innovation process by making them more efficient and provide patients and the public with tools to help and guide them during a pandemic.
What did DRAGON do?
The aim of DRAGON was to increase the capacity of the healthcare system so it can respond to COVID-19 and to future pandemics. To achieve this goal the project achieved four main objectives:
1. Deliver AI models that are based on imaging (such as CT scans) to diagnose and predict the course of COVID-19 and other infectious diseases. These models will support medical decision making and resource planning. These AI models will allow clinicians to diagnose and triage patients by providing a prediction of disease outcome within minutes. Certain features on medical images are impossible to fully assess with the naked eye which can be inaccurate. AI models are far more efficient and accurate than relying solely on the individual doctor.
2. Speed-up the development of new therapies by creating a precision medicine approach. This approach will apply molecular profiling and AI to the models to diagnose and then predict the course of infection and response to individual treatment options.
3. Use a machine learning system that will consider new information to continuously learn and improve. This “Distributed Learning” system, will provide a way of efficiently sharing and analysing data on a large scale. This will increase the capacity for innovation and the speed with which it can happen. By building this data sharing platform we can guarantee increased preparedness for future infection disease outbreaks and the ability to stop a future pandemic in its track before it reaches COVID-19 proportions.
4. Engage stakeholders to develop tools to support personal decision making that will focus on empowering patients and the public. The support tool will consider the whole patient journey and will be built using information and learning from the first three objectives. Research shows that when we put the patient first and we empower individual patients to actively participate in their care, it leads to better patient outcomes overall.
Now that the project has drawn to a close we conclude that DRAGON completed its four main objectives:
1. Delivered Artificial Intelligence (AI) models that are based on imaging (such as CT scans) to diagnose and predict the course of COVID-19 and other infectious diseases. These models can support medical decision making and resource planning.
2. Accelerated the development of new therapies by creating a precision medicine approach. This approach uses AI to diagnose and then predict the course of infection and response to individual treatment options.
3. Used a machine learning system that will consider new information to continuously learn and improve. This “Distributed Learning” system, provides a way of efficiently sharing and analysing data on a large scale. This will increase the capacity for innovation and the speed with which it can happen.
4. Empowered patients and the public to make informed decisions about their healthcare.
The aim of DRAGON was to increase the capacity of the healthcare system so it can respond to COVID-19 and to future pandemics. To achieve this goal the project achieved four main objectives:
1. Deliver AI models that are based on imaging (such as CT scans) to diagnose and predict the course of COVID-19 and other infectious diseases. These models will support medical decision making and resource planning. These AI models will allow clinicians to diagnose and triage patients by providing a prediction of disease outcome within minutes. Certain features on medical images are impossible to fully assess with the naked eye which can be inaccurate. AI models are far more efficient and accurate than relying solely on the individual doctor.
2. Speed-up the development of new therapies by creating a precision medicine approach. This approach will apply molecular profiling and AI to the models to diagnose and then predict the course of infection and response to individual treatment options.
3. Use a machine learning system that will consider new information to continuously learn and improve. This “Distributed Learning” system, will provide a way of efficiently sharing and analysing data on a large scale. This will increase the capacity for innovation and the speed with which it can happen. By building this data sharing platform we can guarantee increased preparedness for future infection disease outbreaks and the ability to stop a future pandemic in its track before it reaches COVID-19 proportions.
4. Engage stakeholders to develop tools to support personal decision making that will focus on empowering patients and the public. The support tool will consider the whole patient journey and will be built using information and learning from the first three objectives. Research shows that when we put the patient first and we empower individual patients to actively participate in their care, it leads to better patient outcomes overall.
Now that the project has drawn to a close we conclude that DRAGON completed its four main objectives:
1. Delivered Artificial Intelligence (AI) models that are based on imaging (such as CT scans) to diagnose and predict the course of COVID-19 and other infectious diseases. These models can support medical decision making and resource planning.
2. Accelerated the development of new therapies by creating a precision medicine approach. This approach uses AI to diagnose and then predict the course of infection and response to individual treatment options.
3. Used a machine learning system that will consider new information to continuously learn and improve. This “Distributed Learning” system, provides a way of efficiently sharing and analysing data on a large scale. This will increase the capacity for innovation and the speed with which it can happen.
4. Empowered patients and the public to make informed decisions about their healthcare.
Despite the numerous warnings of the potential catastrophic effects of an unexpected and novel pathogenic outbreak, the COVID-19 pandemic has revealed that additional innovative steps, beyond simply expanding capacity, resources and coordination, are needed to increase our readiness for and effectiveness during such an infectious disease event. With the aim of upgrading current and future pandemic response capabilities, the application here will integrate AI enhanced imaging and distributed data analysis approaches to develop a universal infrastructure that will:
● Validate the concept that advanced AI techniques extract the central insights from CXR and CT scans to facilitate rapid diagnosis and prognosis.
● Establish proof-of-concept for the use of AI enhanced precision medicine approaches to improve prognosis and accelerate the development of new therapeutics.
● Increase preparedness for individual case management with patient empowerment centered decision support systems.
All publications related to and created from the project remain available pubnlically through: https://europeanlung.org/dragon/publications/(opens in new window)
A few highlighted (more recent) publications that originate from the DRAGON project are:
• Doubts and concerns about COVID-19 uncertainties on imaging data, clinical score, and outcomes
• Automatized lung disease quantification in patients with COVID-19 as a predictive tool to assess hospitalization severity
As a concrete product, partner Thirona developed a specific AI tooling for Chest CT imaging: CAD4Covid, which is now included in their LungQ2.0 Clinical suite supporting pulmonologists in hospitals at an international scale through AI applications platforms. https://thirona.eu/clinical-care/(opens in new window)
Next to this all other public information and created resources from the project are available through: https://europeanlung.org/dragon/public-information-and-resources/(opens in new window) or through the CORDIS project website.
Last but not least, the developed mobile application for patient information is available in google and apple stores, and can be found through our partners’website https://www.comunicare.be/home/(opens in new window)
● Validate the concept that advanced AI techniques extract the central insights from CXR and CT scans to facilitate rapid diagnosis and prognosis.
● Establish proof-of-concept for the use of AI enhanced precision medicine approaches to improve prognosis and accelerate the development of new therapeutics.
● Increase preparedness for individual case management with patient empowerment centered decision support systems.
All publications related to and created from the project remain available pubnlically through: https://europeanlung.org/dragon/publications/(opens in new window)
A few highlighted (more recent) publications that originate from the DRAGON project are:
• Doubts and concerns about COVID-19 uncertainties on imaging data, clinical score, and outcomes
• Automatized lung disease quantification in patients with COVID-19 as a predictive tool to assess hospitalization severity
As a concrete product, partner Thirona developed a specific AI tooling for Chest CT imaging: CAD4Covid, which is now included in their LungQ2.0 Clinical suite supporting pulmonologists in hospitals at an international scale through AI applications platforms. https://thirona.eu/clinical-care/(opens in new window)
Next to this all other public information and created resources from the project are available through: https://europeanlung.org/dragon/public-information-and-resources/(opens in new window) or through the CORDIS project website.
Last but not least, the developed mobile application for patient information is available in google and apple stores, and can be found through our partners’website https://www.comunicare.be/home/(opens in new window)