AI4LUNGS is on a mission to contribute to healthier communities by providing doctors with better tools to personalise treatment for lung diseases. The project aims to potentially increase the quality of patient care and reduce associated costs. This impact will be generated by fostering research with high scientific impact publications and open science, creating new research communities in lung diseases, involving policymakers in promoting the use of AI tools in decision-making for these diseases, and recommending new guidelines as relevant for the new technologies. Moreover, as the project progresses, there are plans to initiate a stakeholder forum and design and implement roll-out strategies that will guarantee the project's continuity beyond the implementation period.
Impact
Project’s pathways towards impact
Technological impact
Scientific impact
Social-clinical impact
Societal impact
Economic impact
Technological impact
The project outcomes will include innovative AI computational disease models to analyse clinical data and support the patient stratification process. Learning from similar patients will lead to more accurate diagnoses and the ability to predict the outcomes of specific treatment strategies for individual patients. Enabled by robust existing infrastructure and data transfer technologies, the tools will be validated and demonstrated in at least two clinical settings. Interoperability of the system architecture allows for expansion to incorporate new data modalities as they become available as well as capacity to work with different health systems across Europe.
Scientific impact
Academic and industrial researchers who seek associations and causality of disease progression will benefit from AI4LUNGS. The DSS (Decision support systems) outputs will shed light on disease causes, progression and response to treatments, by identifying connections among the multiple features in the models. Multi-modal models account for multiple diseases at once, as opposed to current automatic strategies that evaluate each disease separately, ignoring the strong correlations among respiratory diseases when stratifying patients. Combined disease models will identify new connections and have a strong impact on diagnosing and planning the treatment of patients with more than one disease.
Social-clinical impact
AI4LUNGS will research trustworthy interfaces and display of the results to increase acceptance of AI-based decision-support tools in medical practice. The successful uptake of AI4LUNGS will play a part in bringing powerful technologies into daily medical practice, improving standards of care and promoting a healthy society.
Societal impact
AI4LUNGS aims to take part in building healthier societies where health decisions are powered by evidence and data-driven technologies. By automating processes for data transfer and employing existing infrastructure, the system will be inclusive and provide high quality digital services for all – even to small or remote hospitals where manpower to transmit data is not available and few similar patients are being treated. AI4LUNGS prioritises the development of ethical AI-based tools for medicine, providing healthcare systems with greater access to more information about patients’ diagnosis and treatment pathways without compromising patient privacy or rights.
Economic impact
AI4LUNGS aims at fast and more accurate diagnosis, and reduction of erroneous or unnecessary treatment. Scaled-up use of AI4LUNGS will promote more sustainable healthcare and better allocation of resources for diagnosing and treating patients with respiratory diseases. Broad use of AI4LUNGS across longitudinal care, together with geographic scale-up and diffusion in other settings and its replication/customization for more diseases will financially benefit health systems and economies.