Dr Yan Chen

Professor Chen was appointed to the Chair of Digital Screening and is the head of the Digital Cancer Screening Research Group at University of Nottingham, having previously been the Director of the Applied Vision Research Centre at Loughborough University.

Professor Chen has led the development of the world-first national digital assessment and training scheme in radiology (PERFORMS) for breast screening readers which is fully embedded within the UK’s National Breast Screening Programme for more than 34 years in order to help to ensure the quality of radiology reporting and improve readers’ imaging interpretation skills (https://iperforms.com/performs). This platform is endorsed by the Royal College of Radiologists, comprises a mandated activity for radiologists’ annual appraisal and is also accredited by the European accreditation Council for Continuing Medical Education.

Due to its success, her research has been extended in the UK lung cancer screening programme (PERFECTS) which is the first assessment and training platform that aims to ensure appropriate interpretation of lung CT scans in order for radiologists to benefit patient outcome and streamline clinician workload (https://iperforms.com/perfects). It is the external quality assurance for lung screening programme and self-assessment and training to screening readers. The scheme addresses the need for continuous improvement in radiology reporting ability which is vital for any successful screening programme.

Professor Chen has received multiple large research grant awards as PI/Co-I, working closely with national and international organisations, including Horizon 2020, WHO, Innovate Research UK, National Institute for Health Research, and NHS England. Her research interests are in medical imaging, covering cancer screening, early cancer detection, and diagnostic accuracy in CT, breast mammography and tomosynthesis, contrast mammography, and digital pathology specialities. She’s specifically interested in quality assurance of health professionals and Artificial Intelligence (AI) programmes that interpret medical images, as well as using eye tracking technology and developing AI applications to aid health professionals’ training.

Professor Chen is also working on AI evaluation and benchmarking to ensure that AI can be safely implemented into the clinical setting to aid cancer detection, particularly in the screening setting. She advocates risk stratified approaches to screening programmes and is currently involved with the MyPEBS clinical trial, as well as screening technology improvement, such as the potential uptake of breast tomosynthesis in screening, part of the PROSPECTS trial.

She has held various positions, including Honorary Member of Royal College of Radiologists, RSNA Machine-Learning Committee Member, Chair of SPIE Medical Imaging, Associate Editor for British Journal of Radiology and Journal of Medical Imaging.