Fellows' Publications

Fellows have opportunities to publish academically during NHS Fellowship in Clinical AI, particularly relating to their AI project. Explore the fellowship-related publications of our fellows below, newest first.

Fellow Publication
Beyond protected characteristics- rethinking AI fairness through the lens of structural and social determinants of health
Beyond Validation- Operationalising Post-Deployment Surveillance of AI Medical Devices in Clinical Practice
Artificial intelligence and clinical informatics in UK ophthalmology training- a national cross-sectional survey.
Artificial intelligence-assisted reader evaluation in acute CT head interpretation (AI-REACT)- a multireader multicase study
Development and validation of a predictive model for high-intensity mental health service use using electronic health record data
Royal College of Radiologists Guidance Statements on the Use of Auto-contouring in Radiotherapy
Unlocking the potential of Artificial Intelligence- A Guideline for Deployment
An investigation of race bias in deep learning-based segmentation of prostate MRI images
Artificial Intelligence Methods Applied to Electronic Health Record Data for Health Equity in Clinical Trials
TRUST-AI
An opportunity to seize or a threat to mitigate? UK public health specialists’ views on artificial intelligence (AI)
Evaluating the environmental sustainability of AI in radiology- a systematic review of current practice
Artificial intelligence and machine learning in thoracic surgery- A scoping review
Dementia-related volumetric assessments in neuroradiology reports- a natural language processing-based study
A commentary on ophthalmic patients co-designing a new tool to better understand their hospital letters
Making the most of clinical fellowships— robotics, data science and artificial intelligence
The role of procurement frameworks in responsible AI innovation in the National Health Service— a multi-stakeholder perspective
Artificial intelligence and machine learning capabilities in the detection of acute scaphoid fracture— a critical review
Radiology AI training and assessment—challenges, innovations, and a path forward
Guidance on auto-contouring in radiotherapy
Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies- a systematic review
Evaluating the impact of artificial intelligence-assisted image analysis on the diagnostic accuracy of front-line clinicians in detecting fractures on plain X-rays (FRACT-AI)— protocol for a prospective observational study
Revealing transparency gaps in publicly available COVID-19 datasets used for medical artificial intelligence development—a systematic review
Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records— a retrospective modelling study
Beyond regulatory compliance— evaluating radiology artificial intelligence applications in deployment
Deploying artificial intelligence software in an NHS trust— a how-to guide for clinicians
Artificial intelligence and machine learning for clinical pharmacology
Assessing the effectiveness of artificial intelligence (AI) in prioritising CT head interpretation— study protocol for a stepped-wedge cluster randomised trial (ACCEPT-AI)
AI assisted reader evaluation in acute CT head interpretation (AI-REACT)- protocol for a multireader multicase study
A surgical perspective on large language models
Insights and trends review— artificial intelligence in hand surgery
AI chatbots not yet ready for clinical use
The time is now— making the case for a UK registry of deployment of radiology artificial intelligence applications
Using Artificial Intelligence to Stratify Normal versus Abnormal Chest X-rays— External Validation of a Deep Learning Algorithm at East Kent Hospitals University NHS Foundation Trust

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