Professor Gerald Lip is the project lead for Scotland’s GEMINI evaluation - a project evaluating the use of AI in radiology during breast screening. He is a member of the HSE National Screening Service (NSS) AI Strategic Advisory Committee which provides strategic direction, guidance and advice on the implementation and ongoing management of artificial intelligence to NSS programmes, including BreastCheck. Here, he answers some key questions about the future for AI in breast screening.
By Lynne Caffrey, Senior Communications Officer, National Screening Service
What is the GEMINI project?
GEMINI was an evaluation designed to understand the impact of using AI in breast screening as a safety net alongside standard practice. It took place in NHS Grampian, Scotland, between February and October 2023.
We invited around 11,000 women due to attend routine breast screening to take part in the review. All participants received the same standard of care: their mammograms were read independently by two radiologists, with a third reader involved if there was disagreement.
Where a mammogram was given a normal result by the radiologists, AI was switched on to check this reading. If the AI highlighted an area of concern, radiologists reviewed the images again.
What did the evaluation find?
Using AI in this way led to the detection of 10% more breast cancers. These additional cancers were generally small and early-stage - the type that might not have become visible until the woman’s next screening mammogram.
Importantly, these findings were subtle. None of the cancers were obvious on first reading, and all could reasonably have been not seen by human readers alone. The AI acted as an additional safety net rather than a replacement for clinical judgement.
Similar results have been seen elsewhere. For example, the Swedish MASAI trial of 100,000 women found that when AI was used to support screening, 29% more cancers were detected.
In Denmark, AI was introduced to replace one human reader as a solution to recruitment challenges which were causing delays. They screened as usual for 6 months with two human readers, then introduced AI and screened for another 6 months with one human reader and one AI reader. In the 6 months with one human and one AI reader they picked up more cancers, had fewer false positives and reduced the reading workload.
How did women involved in GEMINI feel about AI being used?
Women were largely supportive. Of 15,000 invitation letters sent, only 124 women chose to opt out of the project. Those who did shared a range of concerns, including a general dislike of AI, worries about data use, or fears that radiologists might lose their jobs.
Clear communication helped. Providing clear and transparent information reassured many women that AI was being used in the evaluation safely and responsibly, and always with humans in the loop.
Did AI increase recall rates?
Yes, AI flagged around 1,000 additional cases for review. However, expert human readers carefully assessed these and ultimately recalled only 55 women. From those 55 recalls, 11 additional cancers were diagnosed.
AI can generate false positives, which leads to an increased workload for radiologists. It takes skilled professionals to interpret, filter and act on its results. The most benefit comes from combining AI with human expertise.
So AI won’t replace human readers?
No. AI does not replace radiologists. AI analyses images only. It does not consider a woman’s prior mammograms, clinical and screening history, or individual risk factors when making a decision about her screening results.
Humans provide context, judgement and experience. We can recognise when an anomaly flagged by AI has been stable for years, previously biopsied, or can be explained by clinical information that AI cannot access.
The strongest results come from human–AI collaboration. AI can reduce workload, support consistency, and help prevent the burnout that can be caused by reading a high volume of mammograms and carrying the responsibility for women’s health. It gives radiologists more time and space to apply their expertise.
What are the benefits for women?
One major benefit is faster turnaround times. AI provides an instant second read, rather than waiting for another human reader.
Faster results mean quicker follow-up appointments, reduced waiting times, and less anxiety for women.
There is also growing research interest in AI’s potential to support risk prediction and personalised screening, with early evidence suggesting AI may identify women who could benefit from earlier recall between screening rounds.
What are the common misconceptions about medical AI?
One common misconception is that current medical AI is ‘learning’ continuously like some AI systems, when it is actually a fixed software version. Medical AI used in screening is CE-marked software, which means it meets regulatory, safety and performance requirements. This type of AI delivers fixed, repeatable outputs, while performance can be monitored and calibrated. It does not independently evolve as it is used.
AI is a tool, not a decision-maker. It supports clinicians and makes us better, acting as a reliable ‘second pair of eyes’ or ‘friend over your shoulder’, helping us feel more confident in our decisions.
What’s next for AI in breast screening?
Sweden used to double read its screening mammograms but it is about to switch to having one human plus AI. In the Swedish MASAI trial, AI-supported breast screening detected 29% more breast cancers while potentially halving radiologist workload. Seven EU countries are already using AI in radiology in practice. Norway and the UK are trialling AI. The UK trial is over three years, and its findings will inform future decisions. Countries that use single reading are already using AI.
In the US some people are paying under their health insurance policies to have AI added to their reading. They are paying for a single reader plus AI.
Radiology is leading the way, but lessons learned here will support AI adoption across other clinical specialties, including pathology, scheduling, reporting and patient communication.
There is also potential for research because it offers a good amount of data to harvest, enabling us to look at prediction and personalisation.
Final thoughts
Clinically, the evidence is clear: AI works when used responsibly. However, introducing AI into breast screening is complex. It requires robust infrastructure, governance and careful implementation.
AI is already helping detect cancers today that might otherwise have gone undetected for another 2 or 3 years. Used well, it has the potential to strengthen screening programmes, support staff, and most importantly, improve outcomes for women.
First published in the Medical Independent, 6 April 2026: The future of AI in breast screening
More information:
- GEMINI project – nhsgrampian.org
- MASAI study: AI use in breast cancer screening cuts rate of later diagnosis by 12%, study finds – theguardian.com
- Advancing screening in Ireland: Implementing an AI programme in the National Screening Service
- Artificial Intelligence and population screening – it’s not a case of if but when