School of Health & Wellbeing

Published today in Nature Cancer, the evaluation was carried out by a team of scientists, clinicians and software developers from the University of Aberdeen, NHS Grampian, and Kheiron Medical Technologies, now part of DeepHealth Inc., and was funded through the NHS AI in Health and Care Award in partnership with the National Institute for Health Care Research (NIHR).

The study found that not only did AI help detect more cancers, most of which were invasive and high grade, it could also reduce the time to notify affected women from 14 days to just 3 days.This, the authors say, is hugely significant given that the earlier detection of primarily high-grade cancers enables earlier treatment, which has a greater likelihood of treatment success.

The researchers also found that using AI as part of the large-scale screening programme could reduce the number of women recalled unnecessarily for further assessment including unnecessary biopsies. This, the team say will significantly reduce patient stress and worry while also saving healthcare resources and costs.

The evaluation, led by the University of Aberdeen, followed NHS Grampian's GEMINI (Grampian’s Evaluation of Mia in an Innovative National breast screening Initiative) project which was facilitated by the North of Scotland NHS Innovation Hub.

The team assessed how an AI software tool, Mia, developed by Kheiron, could be used to support healthcare workers in the routine breast screening of 10,889 women in NHS Grampian.

Dr Clarisse de Vries, Lecturer in Data Science at the University of Glasgow, lead author and former Research Fellow at the University of Aberdeen, explains why this GEMINI evaluation is so impactful for thousands of women: “As part of the UK breast screening programme all women aged between 50 and 70 years old in the UK are invited for mammograms every three years. This results in over 2 million mammogram examinations being performed annually.

“Currently, in the UK, to reduce the number of cancers missed, two radiologists read every mammogram. However, some breast cancers are extremely hard to detect, and it is not always clear from mammograms whether breast cancer is present. So, when there is the suspicion of cancer on a mammogram the woman is recalled for additional investigations.

“Despite this, approximately 20% of cancers are missed using this process. Furthermore, many more women are recalled for further assessments than are diagnosed with cancer. For each five women recalled, approximately one will be diagnosed with breast cancer. So, they have had unnecessary, often invasive tests – not to mention the additional worry for the patient.

“This is why our findings are so important – not only did we find optimal ways to detect breast cancer, quicker and more accurately, we also found ways to reduce the number of women having to return for unnecessary tests.”

The study’s findings help address several of the evidence gaps identified by the UK National Screening Committee. While further research is needed to fully quantify the benefits and any potential harms, this work provides an important foundation for next steps in the field. It directly supports the upcoming EDITH trial, which will expand this work to evaluate the use of AI in breast screening across sites throughout the UK. The Scottish element of the trial will be led jointly by the University of Aberdeen, NHS Grampian and University of Glasgow.


First published: 13 March 2026

<< News