Strengthening Health Systems with Digital Innovation and Radiomics

Health systems today face a dual burden of disease:

• Non-Communicable Diseases (NCDs): Responsible for over 70% of global deaths, disproportionately affecting low- and middle-income countries.
• Communicable Diseases (CDs): Ongoing outbreaks and pandemics continue to strain health infrastructures worldwide.

This complex challenge requires smarter, more resilient health systems driven by innovation, data, and rapid response capabilities.

Data-Driven Health Transformation through Radiomics and AI

The digitization of healthcare is generating massive datasets, particularly through medical imaging. These can transform health systems when combined with radiomics and artificial intelligence (AI).

Radiomics?is a method that extracts quantitative data from medical images (MRI, CT, PET), and when integrated with AI and machine learning (ML), enables:

• Early disease detection and risk stratification
• Personalized treatment planning
• Monitoring of therapy response
• Enhanced diagnostic accuracy and efficiency

This approach enables precise, data-driven decision-making across imaging modalities.

Policy Priorities and Strategic Actions

To unlock the benefits of AI and radiomics, policymakers should:

1. Invest in secure, interoperable digital infrastructure for health data.
2. Build capacity in AI, radiomics, and data science within health systems.
3. Foster public–private–academic partnerships for innovation and deployment.
4. Develop ethical and regulatory frameworks for equitable AI use in healthcare.
5. Ensure high data quality and governance for reliable implementation.

Strategic adoption of these tools enhances health system resilience, efficiency, and outcomes, especially in high-burden regions.

AI Against Respiratory Diseases

Outbreaks like COVID-19, SARS, and MERS revealed the need for smarter surveillance and rapid diagnosis.

AI and ML?tools can improve pathogen detection, predict spread, and support evidence-based health planning.

Radiomics?proved crucial during COVID-19 by identifying lung damage faster and more accurately. Applications include:

• Improved diagnosis and triage
• Disease severity prediction
• Planning ICU and ventilator needs

These technologies can optimize care during future outbreaks and make better use of limited health resources.

Why the IAEA?

The IAEA has over 60 years of leadership in nuclear science and medical imaging. Since 1958, it has helped countries apply nuclear medicine and imaging technologies to combat NCDs and CDs.

Key strengths:

• Global imaging expertise and training programmes
• Leadership in over 100 Coordinated Research Projects (CRPs)
• Management of global imaging databases: DIRAC, NUMDAB, IMAGINE

ZODIAC (Pillar 4)?supports a global observatory collecting over 20,000 chest X-rays and 5,000+ CT scans daily to detect respiratory threats and enable rapid response.

IAEA Coordinated Research Project E13054

The ZODIAC Respiratory Disease Phenotype Observatory?is an IAEA-led cooperative study using AI to analyze chest X-rays and CT scans from COVID-19 and other respiratory diseases.

Key goals include:

• Developing AI models to analyze imaging data
• Creating a secure global imaging repository
• Identifying markers of disease severity across populations
• Providing personalized guidance on imaging capacity and planning
• Supporting early pandemic detection and preparedness

Expected impact:

• Smarter clinical decision-making
• Better resource planning and training
• Global research collaboration and health resilience

Through strategic investments in radiomics and artificial intelligence, the IAEA is helping countries prepare for the future of healthcare—smarter, faster, and more resilient in the face of both current and emerging health challenges.