About Us
Designed by the leading experts in their fields
Over 35 years of performance benchmarking
In use in over 15 countries
Covering a wide spectrum of clinical areas including breast, AI, lung and prostate
Quality is our passion
PERFORMS assessment is the world’s first accredited radiological self-assessment programme now. Started in 1991 by Professor Alastair Gale, it is globally acclaimed and has won numerous awards. It is the only clinically validated solution of its kind, substantiated by peer-reviewed publications in high-impact journals.
Over 2000 radiologists have been trained, interpreting 2.4 million exams collectively.
Expertise and Experience
The PERFORMS team comprises leading international experts in medical imaging cognitive and perceptual performance assessment and training. For over 35 years we have worked to improve the diagnostic skills of health professionals to the benefit of patients.
The Team
Yan Chen
Professor of Digital Screening
Bev
Projects Officer
Eleni
Team Leader
Sjors
Development Lead Engineer
Adnan
Clinical Research Fellow
Iain
Senior Research Fellow
George
Senior Research Technician
Bob
Development Lead Engineer
Lavender
Senior Technician
Rongjun
Digital Research Technician
Harry
Lab Technician
The team is a rapidly expanding medical imaging research group within the Translational Medical Sciences at the University of Nottingham. Composed of Researchers, Project Managers, and Coordinators, we focus on high-quality assessment and training to enhance diagnostic skills.
For over 35 years, we enhance image interpretation for screening programmes and radiologists, ensuring diagnostic precision. Our NHS-compliant certification reduces litigation risks.
To enhance cancer detection rates and recall accuracy in screening programmes, assessing team performance is crucial. We provide feedback to uplift underachievers, ensuring uniform high standards.
Demographics, bias, overfitting, and compatibility are barriers to AI adoption. Learn how our customised solution can effectively train and assess AI algorithms.
