Lung diseases represent a diverse and complex group of illnesses that have a profound impact on global health and economies. Each year, these diseases cause severe illness to hundreds of millions and are responsible for the deaths of millions worldwide, accounting for over 10% of all disability-adjusted life-years (DALYs). They also impose a substantial economic burden, draining more than €380 billion annually from the EU economy. Lung cancer, in particular, stands out for its high mortality rate globally. One of the primary challenges in treating lung disease is the wide array of possible conditions, many of which present with similar symptoms and affect the lungs in similar ways. Often, patients may suffer from multiple, interconnected lung diseases, further complicating diagnosis and treatment. Traditional clinical approaches require extensive multidisciplinary teams and a range of diagnostic tools, leading to increased costs, time, and resource use. There is a pressing need for digital solutions that can streamline this process, offering faster, more accurate diagnoses and treatment plans. ‘AI is perhaps the most transformational technology of our time, and healthcare is perhaps AI’s most pressing application.’ -Satya Nadella, chief executive officer, Microsoft At Future Needs, participation in the AI4Lungs project is embraced through involvement in various Work Packages such as “Project Management”, “End-User Co-Design, System Architecture and Framework Analysis”, “Legal and Ethical Issues”, “Algorithm Validation, Pilot Testing and Assessment”, and “AI4Lungs Platform, Digital Twin Service and User Experience”. Leadership is provided in the critical Work Package of “Dissemination, Communication, Sustainable Exploitation“. Our contribution spans across multiple critical domains, ensuring the project aligns with regulatory and ethical standards. Involvement in the AI4Lungs project is characterised by a comprehensive approach, with pilot testing and assessment of AI tools being conducted to evaluate their effectiveness in real-world scenarios. Future Needs plays a key role in ensuring the AI4Lungs platform meets both user needs and technical specifications. Our involvement in the Digital Twin service design and implementation focuses on optimising the user experience, with a dedicated effort towards ensuring end-user co-design principles are upheld, thereby aligning solutions closely with the needs of clinicians and patients. Furthermore, our team is responsible for analysing and defining the system’s architecture and framework, emphasising robustness and scalability. Leading the project’s impact maximisation, Future Needs spearheads strategic approaches for the sustainable exploitation of AI4Lungs outcomes. This includes a significant contribution to Health Technology Assessment (HTA), where we evaluate the technology’s impact on healthcare systems, focusing on usability, cost-effectiveness, and standard of care enhancements. Future Needs is also in charge of mapping the stakeholder ecosystem, ensuring effective communication and engagement through digital tools. Our team is integral in assisting in designing and implementing user-friendly interfaces for the decision support system. Ethical assessments and monitoring are rigorously overseen, with a strong focus on promoting awareness around ethical, legal, and social implications (ELSI). In addition, we lead project branding and communication efforts, organise and host the EU Summit on OneHealth, and develop a TRL9 roadmap, guiding innovation and exploitation. Lastly, our commitment extends to promoting the project’s uptake and sustainability, with a focus on regulatory compliance, intellectual property protection, economic assessment, and health technology assessment, ensuring the longevity and widespread adoption of AI4Lungs’ results.
AI4Lungs is at the forefront of addressing the aforementioned challenges. The project focuses on developing and validating state-of-the-art AI-based tools and computational models to enhance patient stratification, thereby optimising the diagnosis and treatment of both infectious and non-infectious respiratory diseases. These diseases require comprehensive and repeated assessments over time to accurately characterise a patient’s condition. AI4Lungs is designed to be seamlessly integrated into existing clinical pathways, aiding clinicians and stakeholders in decision-making from the initial suspicion of a disease to its diagnosis and subsequent treatment planning. The initiative leverages a wide array of data, including medical records, imaging data, and novel inputs from digital stethoscopes and -omics. By incorporating structured and unstructured data modalities, AI4Lungs‘ stratification strategy aims to position patients more accurately, enabling them to benefit from shared global data and knowledge at all care stages. This approach not only promises to enhance diagnosis and treatment planning but also to extend these benefits to patients in any location, regardless of the remoteness or size of their healthcare facility. The broader impact of AI4Lungs includes reducing healthcare system costs by minimising unnecessary testing and ineffective treatments, thereby optimizing the use of health technologies and resources. By focusing on respiratory diseases, AI4Lungs addresses a set of disorders with a significant disease burden. The project’s innovative approach of combining AI with real-world data and holistic disease modelling offers a more efficient allocation of resources, making the best treatment options accessible to a wider range of patients. AI4Lungs is committed to adhering to FAIR principles and relevant regulatory and ethical guidelines, ensuring responsible and sustainable healthcare advancements. In the long term, the methodologies and tools developed in AI4Lungs have the potential to be applied to other disease classes, sectors, and various value chains, including pharmaceuticals, medical devices, clinical trials, and policy-making. This positions AI4Lungs not just as a solution for current challenges but also as a foundational platform for future innovations in healthcare. AI4Lungs aims to push the boundaries of AI in healthcare by developing novel strategies for data integration and analysis. This includes ensemble methods for predictive modelling, addressing data sparsity and anomalies, studying causality in disease progression, and implementing advanced imaging analytics. The project emphasises the use of AI for holistic patient stratification, utilising innovative techniques like deep learning, cloud-based big data platforms, and natural language processing. The focus on trustworthy and explainable AI will enhance the reliability and acceptance of AI systems in healthcare. The project’s ultimate ambition is to reach a high technology readiness level (TRL), ensuring that the developed systems are practical, effective, and ready for widespread clinical use. Key Objectives:
Lung diseases represent a diverse and complex group of illnesses that have a profound impact on global health and economies. Each year, these diseases cause severe illness to hundreds of millions and are responsible for the deaths of millions worldwide, accounting for over 10% of all disability-adjusted life-years (DALYs). They also impose a substantial economic burden, draining more than €380 billion annually from the EU economy. Lung cancer, in particular, stands out for its high mortality rate globally. One of the primary challenges in treating lung disease is the wide array of possible conditions, many of which present with similar symptoms and affect the lungs in similar ways. Often, patients may suffer from multiple, interconnected lung diseases, further complicating diagnosis and treatment. Traditional clinical approaches require extensive multidisciplinary teams and a range of diagnostic tools, leading to increased costs, time, and resource use. There is a pressing need for digital solutions that can streamline this process, offering faster, more accurate diagnoses and treatment plans. ‘AI is perhaps the most transformational technology of our time, and healthcare is perhaps AI’s most pressing application.’ -Satya Nadella, chief executive officer, Microsoft At Future Needs, participation in the AI4Lungs project is embraced through involvement in various Work Packages such as “Project Management”, “End-User Co-Design, System Architecture and Framework Analysis”, “Legal and Ethical Issues”, “Algorithm Validation, Pilot Testing and Assessment”, and “AI4Lungs Platform, Digital Twin Service and User Experience”. Leadership is provided in the critical Work Package of “Dissemination, Communication, Sustainable Exploitation“. Our contribution spans across multiple critical domains, ensuring the project aligns with regulatory and ethical standards. Involvement in the AI4Lungs project is characterised by a comprehensive approach, with pilot testing and assessment of AI tools being conducted to evaluate their effectiveness in real-world scenarios. Future Needs plays a key role in ensuring the AI4Lungs platform meets both user needs and technical specifications. Our involvement in the Digital Twin service design and implementation focuses on optimising the user experience, with a dedicated effort towards ensuring end-user co-design principles are upheld, thereby aligning solutions closely with the needs of clinicians and patients. Furthermore, our team is responsible for analysing and defining the system’s architecture and framework, emphasising robustness and scalability. Leading the project’s impact maximisation, Future Needs spearheads strategic approaches for the sustainable exploitation of AI4Lungs outcomes. This includes a significant contribution to Health Technology Assessment (HTA), where we evaluate the technology’s impact on healthcare systems, focusing on usability, cost-effectiveness, and standard of care enhancements. Future Needs is also in charge of mapping the stakeholder ecosystem, ensuring effective communication and engagement through digital tools. Our team is integral in assisting in designing and implementing user-friendly interfaces for the decision support system. Ethical assessments and monitoring are rigorously overseen, with a strong focus on promoting awareness around ethical, legal, and social implications (ELSI). In addition, we lead project branding and communication efforts, organise and host the EU Summit on OneHealth, and develop a TRL9 roadmap, guiding innovation and exploitation. Lastly, our commitment extends to promoting the project’s uptake and sustainability, with a focus on regulatory compliance, intellectual property protection, economic assessment, and health technology assessment, ensuring the longevity and widespread adoption of AI4Lungs’ results.
AI4Lungs is at the forefront of addressing the aforementioned challenges. The project focuses on developing and validating state-of-the-art AI-based tools and computational models to enhance patient stratification, thereby optimising the diagnosis and treatment of both infectious and non-infectious respiratory diseases. These diseases require comprehensive and repeated assessments over time to accurately characterise a patient’s condition. AI4Lungs is designed to be seamlessly integrated into existing clinical pathways, aiding clinicians and stakeholders in decision-making from the initial suspicion of a disease to its diagnosis and subsequent treatment planning. The initiative leverages a wide array of data, including medical records, imaging data, and novel inputs from digital stethoscopes and -omics. By incorporating structured and unstructured data modalities, AI4Lungs‘ stratification strategy aims to position patients more accurately, enabling them to benefit from shared global data and knowledge at all care stages. This approach not only promises to enhance diagnosis and treatment planning but also to extend these benefits to patients in any location, regardless of the remoteness or size of their healthcare facility. The broader impact of AI4Lungs includes reducing healthcare system costs by minimising unnecessary testing and ineffective treatments, thereby optimizing the use of health technologies and resources. By focusing on respiratory diseases, AI4Lungs addresses a set of disorders with a significant disease burden. The project’s innovative approach of combining AI with real-world data and holistic disease modelling offers a more efficient allocation of resources, making the best treatment options accessible to a wider range of patients. AI4Lungs is committed to adhering to FAIR principles and relevant regulatory and ethical guidelines, ensuring responsible and sustainable healthcare advancements. In the long term, the methodologies and tools developed in AI4Lungs have the potential to be applied to other disease classes, sectors, and various value chains, including pharmaceuticals, medical devices, clinical trials, and policy-making. This positions AI4Lungs not just as a solution for current challenges but also as a foundational platform for future innovations in healthcare. AI4Lungs aims to push the boundaries of AI in healthcare by developing novel strategies for data integration and analysis. This includes ensemble methods for predictive modelling, addressing data sparsity and anomalies, studying causality in disease progression, and implementing advanced imaging analytics. The project emphasises the use of AI for holistic patient stratification, utilising innovative techniques like deep learning, cloud-based big data platforms, and natural language processing. The focus on trustworthy and explainable AI will enhance the reliability and acceptance of AI systems in healthcare. The project’s ultimate ambition is to reach a high technology readiness level (TRL), ensuring that the developed systems are practical, effective, and ready for widespread clinical use. Key Objectives:
AI-Based Personalised Care for Respiratory Disease using Multi-Modal Date in Patient Stratification
Which issues of today’s digital world does the AI4Lungs project address?
What is the role of Future Needs?
What is the aim of the AI4Lungs project?
Which are the main objectives of AI4Lungs?
Project Facts
AI-Based Personalised Care for Respiratory Disease using Multi-Modal Date in Patient Stratification
Which issues of today’s digital world does the AI4Lungs project address?
What is the role of Future Needs?
What is the aim of the AI4Lungs project?
Which are the main objectives of AI4Lungs?
Project Facts
