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April 5, 2026EULAR Rheumatology Open2 citationsOpen Access

Artificial intelligence in rheumatology and paediatric rheumatology: insights from an international survey by EMEUNET

SBSaverio La BellaARAna Isabel Rebollo-GiménezKAKrystel Aouad

Key Points

  • This research aims to explore the use, perceptions, and concerns regarding artificial intelligence in rheumatology and paediatric rheumatology among professionals.
  • Administered a web-based survey targeting rheumatology professionals worldwide.
  • Survey included sections on participant characteristics, AI use, opinions, and concerns.
  • Responses were collected from March to July 2025 in collaboration with international rheumatology societies.
  • A total of 461 responses gathered from 59 countries, predominantly from trained physicians in Europe.
  • 86.7% of participants reported using AI, particularly for grammar correction and brainstorming tasks.
  • While optimism about AI's potential was high (79.6%), only 13.7% rated their knowledge as strong or expert-level.
  • Main concerns included ethics, trust issues, and insufficient training, with regional disparities noted.

Abstract

Objectives: Artificial intelligence (AI) is revolutionising medicine.The aim of this study was to detail its use, opinions, knowledge, and concerns in rheumatology and paediatric rheumatology.Methods: A web-based survey open to all professionals working in the field was developed by the Emerging EULAR Network (EMEUNET) and disseminated between March and July 2025 in collaboration with other international rheumatology societies (AFLAR, ArLAR, CARRA, PAFLAR, PANLAR).The survey was divided into 4 sections: (i) participants' characteristics, (ii) AI use and applications, (iii) opinions and knowledge, and (iv) concerns, needs, and expectations.Results: Overall, 461 responses were collected from 59 countries.Respondents were mostly physicians who completed their training (316, 68.7%) and were based in Europe (170, 36.9%).Most participants (397, 86.7%) used AI for medical purposes, especially large language models (385, 83.7%) for grammar correction and brainstorming.Although there was broad optimism about its use (366, 79.6%), self-reported practical skills were predominantly basic or still in development (346, 75.1%), and knowledge was rarely defined as strong or expert-level (63, 13.7%).Concerns focused on ethics (314, 69%), lack of trust (316, 69.5%), and insufficient training (270, 59.3%).Disparities emerged across geographic regions in use, knowledge, and practical skills.Conclusions: AI is widely used and positively perceived in rheumatology, despite limited knowledge and practical skills, and regional disparities.Addressing gaps in ethics, transparency, and insufficient training through targeted education and implementation strategies will be essential to ensure an equitable and effective integration into clinical and research practice.

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Cite This Study

Bella et al. (2026) studied this question.

synapsesocial.com/papers/69d1fc4fa79560c99a0a1e05https://doi.org/10.1016/j.ero.2026.03.001
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