The European Society of Radiology (ESR) said that it regrets the European Union (EU) decision to reduce projected funding for a variety of upcoming health and research projects.
The EU's decision, made on 21 July as EU leaders reached an agreement on the budget for COVID-19 recovery and the Multiannual Financial Framework (MFF), will take a toll on European research and will hinder its potential to become an innovation hub for artificial intelligence (AI) and healthcare in the future, according to the ESR.
The agreement resulted in proposed cuts for EU health and research budgets, including a reduction from 94.4 billion euros to 80.9 billion euros for Horizon Europe -- the EU's next research and innovation framework program. Furthermore, proposed funding was also significantly reduced for both the Digital Europe program, which aims to boost investments in AI and make the EU a frontrunner in the sector, and the newly proposed EU4Health program intended to prepare for the next pandemic, the ESR said.
"This step backwards will take a toll on making Europe a research and innovation hub and on improving digital capacities across the European Union," the ESR wrote. "The ESR has consistently called for AI and health data to be used to its full potential, for more integrated and person-centred approaches, a coordinated action on non-communicable diseases and for medical imaging to have a key role in cancer screening, detection and early diagnosis. Nevertheless, these ambitions will be difficult to achieve with plummeting health and research budgets at EU level."
The full ESR statement can be found on the society's website.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=100&q=70&w=100)
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
