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Perspective: large language models and antimicrobial resistance among migrants: an equity imperative

  • Infection Innovation Consortium Interdisciplinary Antimicrobial Resistance Network
  • , Ji Soo Choi
  • , Daniel Pan
  • , Anthony O'Hare
  • , Catrin E. Moore
  • , Fouad M.Fouad
  • , Manish Pareek
  • University of Leicester
  • NIHR Leicester Biomedical Research Centre
  • University Hospitals of Leicester NHS Trust
  • University of Stirling
  • University of London

Research output: Contribution to journalArticlepeer-review

Abstract

Despite progress in antimicrobial resistance (AMR) surveillance, migrants and ethnic minorities, who bear disproportionate AMR burdens, remain underrepresented in programmes. Digital health is common, but we found no interventions using large language models (LLMs) to reduce AMR in these communities. In three workshops, we identified priorities: culturally and linguistically inclusive design; context specific knowledge from community settings; and trust building via community health workers, with data protection and bias mitigation.
Original languageEnglish
Journalnpj Digital Medicine
Early online date14 May 2026
DOIs
Publication statusE-pub ahead of print - 14 May 2026

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