2nd AI4LUNGS Synergy Meeting! 10 EU Projects Come Together for Knowledge Exchange
On 21 October, AI4LUNGS, joined by 9 other EU funded projects, gathered together 35 technical and clinical experts to exchange knowledge, share research developments, and explore opportunities for collaboration. With 13 pitch presentations covering two key themes: New AI Models in Healthcare and System Evaluation and Testing in Clinical Settings.
The meeting was attended by these projects: AI4LUNGS, COMFORT, CoMPaSS-NMD, dAIbetes, Microb-AI-ome, TOLIFE, MultiPulm, SPACETIME, and LUCIA,.
Exploring New AI Models in Healthcare
The first part of the meeting focused on innovative AI models and digital health solutions addressing a wide range of clinical needs. Presentations explored how AI can support disease diagnosis, patient monitoring, treatment outcome prediction, and more personalised approaches to healthcare.
Topics included:
Respiratory health: Respiratory symptom analysis using digital stethoscope data, clinical decision support systems for respiratory diseases, and AI models for monitoring COPD exacerbation risk in free-living settings.
AI-assisted diagnosis: Renal mass segmentation and diagnosis, alongside prostate tumour characterisation within the COMFORT pipeline.
Federated learning: Modelling approaches and research into the effects of cohort interactions on federated colorectal cancer (CRC) prediction.
Treatment outcome prediction: Virtual Human Twin (VHT) approaches for predicting treatment outcomes in type 2 diabetes (T2D).
Digital health and therapeutics: MultiPulm's wellbeing monitoring and voice assessment tools, as well as breathing games exploring the potential of serious games as digital therapeutics.
Together, these presentations demonstrated AI applications being explored across healthcare, from diagnostic support and disease monitoring to treatment prediction and digital therapeutics. They also offered opportunities to compare approaches, identify common challenges, and discuss how research activities across different projects could complement and strengthen one another.
From AI Innovation to Clinical Validation
Developing innovative AI models is only one part of the journey towards meaningful healthcare applications. Equally important is understanding how these systems can be evaluated, validated, and tested in clinical settings, and how their results can be interpreted by healthcare professionals.
The second theme focused on the practical and clinical dimensions of system evaluation, with presentations addressing three important areas:
AI4LUNGS: System validation and assessment design and preparation.
CoMPaSS-NMD: How clinicians assess and interpret the results obtained from AI-based systems.
TOLIFE: The clinician's perspective on clinical studies.
These discussions highlighted the importance of connecting technological development with clinical practice. Understanding how AI systems perform, how their results are interpreted, and how they fit into clinical workflows is essential to building trust and supporting their successful adoption.
Why Synergy Meetings Matter
Healthcare challenges are complex, and addressing them often requires expertise that extends beyond the boundaries of a single project. Although individual EU-funded projects pursue different objectives, they frequently encounter similar technical, methodological, and clinical challenges.
By exchanging knowledge, sharing experiences, and discussing different approaches, projects can build on one another's work rather than operate in isolation. These interactions can help identify complementary research activities, inspire new ideas, reduce duplication of effort, and open doors to future collaborations.
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