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AI4LUNGS is a three-and-a-half-year European research and innovation project with the primary objective of creating and validating AI tools and computational models to improve patient stratification, ultimately optimizing the diagnosis and treatment of respiratory diseases - Interstitial Lung Diseases (ILDs), Infectious Diseases and cancer. 

It aims to support physicians in their decision-making during the diagnosis and treatment processes, streamlining and digitalising procedures, potentially saving time, and reducing the need for numerous examinations compared to traditional approaches. The feasibility and efficiency of the developed solutions will be evaluated in 2 pilots.

The project is in the domain of the tools and technologies for a healthy society, on developing new AI tools, using different types of data collected in clinical practice, e.g., lung auscultation, X-ray, CT, PET, clinical analysis, demographic, and clinical data.



AI4LUNGS innovates on two fronts: developing technologies to improve the devices and tools used in diagnosis decisions and integrating all the new tools in a single platform (digital-twin) capable of monitoring and advising during the entire clinical decision. 


Two novel technologies

AI4LUNGS introduces two novel technologies to the medical field: digital auscultation and early-stage liquid biopsy in the decision support systems, where the second one aims to identify cancer types more efficiently and reduce unnecessary examinations, thereby speeding up the diagnosis process and cutting costs.


Virtual Digital Twin

The project will develop a virtual digital twin to provide an example of the AI4LUNGS platform interface with embedded patient history, current status, performance, and examples of the results achieved by all the models that will be developed in the project. The digital twin will be a major step towards precision and personalised medicine offering the potential for use in clinical training. 

Objectives and ambition

The  AI4LUNGS consortium combines innovations, moving from Lab to Hospital level, creating an ecosystem of R&D with an international multidisciplinary team, empowered with the capacity to bring results to market.


Design and build a guideline-based decision support system with explicit easy to understand recommendations to clinicians and other stakeholders based on all the data being gathered along the stratification process.


Develop a set of integrated and interpretable computational models using AI to spearhead a transition from mere data-fitting and fragmented disease models to holistic models that will help to diagnose and plan the treatment of respiratory diseases. 


Integrate novel data modalities: a) new modality lung auscultation recordings from digital stethoscope examination and b) new uses for -omics biomarkers. 


Design, develop and deploy a secure, easy-to-integrate and scalable infrastructure based on industry-accepted protocols that will manage and process data according to the GDPR, FAIR principles, ethical principles as well as hospital-specific information and communication rules.


Design a personalised interactive dashboard based on trustworthy human-digital interaction.


Create an open-access data repository to foster research on respiratory diseases across Europe and beyond


Demonstrate and validate the AI4LUNGS tools creating a strong synergy with the medical stakeholders to potentially improve the system's performance and usability.


Measure the impact on the clinical pathway’s usability, trustworthiness, improved standard of care, time reduction, cost reduction, etc.


Maximize impact and design a sustainable exploitation strategy by adopting a pro-active and professional knowledge management to create the foundations for generating impact, balancing dissemination and IP protection.


Analyse and create awareness of AI4LUNGS Ethical, Legal and Social Implications (ELSI) to ensure responsible development by continuously addressing ethical, legal, clinical policies and social issues


The AI models that will be developed during the project will be validated using retrospective data collected from five consortium partners. AI algorithms’ results validation will be done in collaboration with data scientists at the medical centers. After the validation of individual algorithms, these will be integrated to work as a single system for further validation with clinicians until the end of the project. 
AI4LUNGS aims to reach the next level and integrate this combination of model and AI-based methods in a single platform and perform a pilot demonstration of the full system. To test this in an operational scenario, observational studies will be run in at least two hospitals in two countries using prospective data of patients with lung cancer, interstitial disease, and covid.

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