119 posters, 6 topics, 524 authors, 243 institutions
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RCR Global AI Conference 2026
29-30 June, 2026 | QEII Centre, Westminster
140
<p>Augmenting Emergency Imaging Decisions: Performance of a Custom Large-Language-Model Decision Support System for SHOs in Time-critical Medical Emergencies</p>
Poster Presenter
Authors
Ebinesh Arulnathan, Praislin Gideon, Shirou Masoodi, Swetha Tula, Matthew Kueh, Rayya Naffa', Sivakumar Manickam , Mohammad Shoaib
Affiliations
East & North Hertfordshire, Mid & South Essex NHS trust , Mid and South Essex NHS Foundation Trust, Alder Hey Children's NHS Foundation Trust , Royal Free London NHS Foundation Trust, University Hospital Southampton NHS Foundation Trust,
Part of Topic
Transforming practice and leadership: pilot or test data on implementation of AI into clinical practice, clinical feedback or patient perspectives
Augmenting Emergency Imaging Decisions: Performance of a Custom Large-Language-Model Decision Support System for SHOs in Time-critical Medical Emergencies
A custom, guideline-curated LLM can function as a high-yield emergency imaging request scaffold. The safest and most effective operating model is supervised augmentation: the SHO retains clinical responsibility while the model reduces omissions and improves protocol specificity.