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RCR Global AI Conference 2026

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119 posters, 6 topics, 524 authors, 243 institutions

ePostersLive by SciGen Technologies S.A. All rights reserved.

RCR Global AI Conference 2026

29-30 June, 2026 | QEII Centre, Westminster

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Thumbnail for <p>A framework for validation and integration of Multi-Pathology AI outputs in real-world radiology reports</p>

174

<p>A framework for validation and integration of Multi-Pathology AI outputs in real-world radiology reports</p>

Carlos Schorlemmer, Christian Gottfried Völker, Ernest Montana

Unilabs, Unilabs TMC, Unilabs Norway

Poster Presenter: Carlos Schorlemmer

Thumbnail for <p>Aesclepian Vision: - An Offline End-to-End Platform for Unified DICOM Acquisition, Archiving, and AI-Driven Paediatric MRI and CT Analysis with Modular, Clinically Integrated Workflows</p>

176

<p>Aesclepian Vision: - An Offline End-to-End Platform for Unified DICOM Acquisition, Archiving, and AI-Driven Paediatric MRI and CT Analysis with Modular, Clinically Integrated Workflows</p>

Ramandeep Kang

Alder Hey Childrens Hospital

Poster Presenter: Ramandeep Kang

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Thumbnail for <p>Integrating a LLM-Based Tool into Emergency CT Workflow: Enhancing Trainee Vetting and Protocolling in the NHS</p>

177

<p>Integrating a LLM-Based Tool into Emergency CT Workflow: Enhancing Trainee Vetting and Protocolling in the NHS</p>

Matthew Kueh, Ebinesh Arulnathan, Sivakumar Manickam

Mid and South Essex NHS Foundation Trust, Alder Hey Children's NHS Foundation Trust , University Hospital Southampton NHS Foundation Trust, University Hospital Southampton NHS Foundation Trust

Poster Presenter: Matthew Kueh

Thumbnail for <p>Training Minds for Machine Age Imaging: Medical Students’ Needs, Ethics, and Expectations for Safe AI Integration in Radiology</p>

178

<p>Training Minds for Machine Age Imaging: Medical Students’ Needs, Ethics, and Expectations for Safe AI Integration in Radiology</p>

Roshni Das, Ebinesh Arulnathan, Sivakumar Manickam

Mid & South Essex NHS trust , Alder Hey Children's NHS Foundation Trust , King’s College London

Poster Presenter: Roshni Das

Thumbnail for <p>Accuracy of a Large Language AI Model for MRI Brain Interpretation</p>

180

<p>Accuracy of a Large Language AI Model for MRI Brain Interpretation</p>

Saranya Baleswaran, Rahul Khamar, Rachelle Rachmat, Kasim Alimohamed

Guy's and St Thomas' NHS Foundation Trust, Guy's and St Thomas' NHS Foundation Trust

Poster Presenter: Saranya Baleswaran

Thumbnail for <p>Deep Learning Analysis of Breast Arterial Calcification to Enhance Cardiovascular Risk Prediction in Women</p>

181

<p>Deep Learning Analysis of Breast Arterial Calcification to Enhance Cardiovascular Risk Prediction in Women</p>

Mu'ath Ibrahim, Ziba Gandomkar, Mo'ayyad Suleiman, Mary Rickard, Seyedamir Tavakoli Taba, Patrick Brennan

University of Sydney

Poster Presenter: Patrick Brennan

Thumbnail for <p>Pilot Evaluation of a Custom GPT Model for Automated Quality Assurance of PET-CT Reporting</p>

182

<p>Pilot Evaluation of a Custom GPT Model for Automated Quality Assurance of PET-CT Reporting</p>

Jack Sheppard, Craig George-McDowall, Dafydd Ap Emyr, Alex Powles

Health Education and Improvement Wales / Swansea Bay University Health Board, Swansea Bay University Health Board

Poster Presenter: Jack Sheppard

Thumbnail for <p>Crossing the valley of death: A multi-disciplinary approach for successful AI implementation</p>

183

<p>Crossing the valley of death: A multi-disciplinary approach for successful AI implementation</p>

Emily Redpath, Alex Pavlyuk, Yussefa Sanyang, Goosie Leung, Ayah Mousa, Nikolaos Papadakos, Clarrissa Sanders, Alban Killingback

St George's University Hospitals NHS Foundation Trust

Poster Presenter: Emily Redpath

Thumbnail for Self-Directed Multimodal AI: Multi-Turn Reasoning Vision-Language Models for Rare Brain Pathology

184

Self-Directed Multimodal AI: Multi-Turn Reasoning Vision-Language Models for Rare Brain Pathology

Duaa Alim, Liam Chalcroft

Imperial College London, University College London

Poster Presenter: Duaa Alim

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Topics Sessions

AI Education and research: examples of proof of concept or AI in development, technical advances, teaching approaches or pre-clinical testing(41)AI vigilance ??? Post-implementation monitoring, real world performance evaluation, health economic evaluation(6)AI vigilance – Post-implementation monitoring, real world performance evaluation, health economic evaluation(7)General / other that does not fit into the above(3)Risk management and compliance: projects around governance, compliance and/or ethics and societal impact(13)Transforming practice and leadership: pilot or test data on implementation of AI into clinical practice, clinical feedback or patient perspectives(49)