1

Why the project matters

The COVID-19 pandemic highlighted shortcomings in healthcare systems and the lack of a plan to ensure comprehensive access to care, which was already evident due to ageing, shortage of healthcare personnel, inadequacy of organization in some Mediterranean countries. In Lebanon, in 2020, the percentage of households struggling to access healthcare rose from 25% to 36% and hospitalizations for surgeries decreased by 30% in 2021. Additionally, over 20% of nurses and 40% of doctors have left the country, exacerbating the workforce shortage. Europe is also experiencing a decline in the quality of healthcare systems and socio-economic conditions. For instance, the Huelva province (Spain) has a 20% mortality rate and, despite being highly industrialised, the population has a low socio-economic status. Therefore, the project will promote a transnational collaboration between research and business to turn AI-based innovation into real healthcare solutions.

2

What it aims to achieve

• To support innovation-driven growth in the field of predictive medicine and digital healthcare combined with AI.
• To strengthen innovation capacity through the establishment of transnational academia and business network to develop AI-driven tools aimed at improving the quality of healthcare services.

3

Expected change

• A transnational innovation network linking researchers, companies, and health professionals to co-develop AI-based healthcare solutions.
• Advanced training programs that build cross-disciplinary skills in technology, medicine, and business.
• AI tools and business models ready for real-world use, improving predictive medicine and health crisis response across the Mediterranean.

4

What the project delivers

• A comprehensive needs assessment and stakeholder mapping to identify key challenges and opportunities in healthcare.
• Development of a digital platform for seamless knowledge exchange across research, business, and healthcare sectors.
• Creation of tailored informational materials for diverse stakeholders, enhancing understanding of AI in healthcare.
• Execution of targeted awareness campaigns to educate stakeholders about the potential of AI in predictive medicine.
• Increased awareness among stakeholders about AI applications in healthcare and predictive medicine.
• Analysis and evaluation of the regulatory framework surrounding AI in the healthcare sector.
• Co-development and piloting of AI-driven healthcare solutions, demonstrating their effectiveness in real-world applications.

5

Who benefits

• Universities and Research Centres – At least 5 medical universities will be targeted through clinical partner networks to enhance the translation of research into healthcare applications.
• Healthcare Providers – At least 5 healthcare institutions and 100 healthcare professionals will be involved, benefiting from improved workflow management and the adoption of new technologies.
• Digital Healthcare Enterprises – At least 20 enterprises will join the transnational network, gaining access to innovations and receiving training to meet market demands.
• Patients with Chronic Conditions – The project will impact over 75% of the population at risk, improving early diagnosis and healthcare access for patients.
• Policy Makers and Health Authorities – At least 5 national, regional, and local health authorities will be engaged, receiving scientific evidence and guidance to shape healthcare policies.
• Patient Associations and Citizens – At least 1 patient association per country will be targeted for training and dissemination of the project’s benefits, reaching a broader audience.