Wednesday, 27 May 2026, 3:34 pm
Press Release: Science Media Centre
The government is choosing a mammogram-reading AI tool to
test and validate, ahead of a planned roll out early next
year.
The tool will ease clinician workloads by doing
one of the two independent reads currently required during
mammogram assessment, the government says. They emphasise
that all diagnoses and follow-up decisions will continue to
include qualified health professionals.
The Science
Media Centre asked experts to comment.
Associate
Professor Catherine Shi, Head of the Department of Data
Science & AI, AUT, comments:
“This is a very
positive step for New Zealand and shows increasing maturity
in translating AI research into real healthcare
applications. Breast screening programmes generate extremely
high workloads for radiologists, and AI tools like this have
strong potential to improve screening efficiency and help
detect subtle abnormalities that may otherwise be
missed.
“It is particularly encouraging to see the
project being developed alongside healthcare professionals
and integrated into existing clinical workflows, because
successful healthcare AI deployment depends not only on
model accuracy, but also on how clinicians interpret, trust,
and use the system safely in everyday
practice.”
Conflict of interest statement: “I
declare no real or potential conflict of interest with this
project.”
Dr Nicholas Knowlton, Senior Lecturer
in Statistics, Massey University, comments:
“The
use of AI as a second reader in mammography is timely and,
in my view, relatively low risk when implemented properly.
The key point is that this is not AI replacing radiologists
or making treatment decisions. It is a decision-support
tool. Like spell check, it can flag what it thinks it sees,
but a human still must use clinical
judgement.
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“Radiologists already use software tools
to manipulate images, improve contrast, and help visualise
structures in the breast. AI adds another layer by
indicating which image features may be suspicious or worth
closer attention. The final interpretation still sits with
the radiologist. Patients are still being assessed by a
doctor.
“The more important risk is not the tool
itself, but the governance of the data behind it. New
Zealand has high-value public mammography data. If that data
are allowed to leave the country and contribute to the
development or improvement of commercial AI systems
overseas, while New Zealand researchers cannot access
comparable data to build local capability, then we are
effectively exporting public value.
“These datasets
are not just technical assets. In Aotearoa, they include
information from our communities and should be treated as
taonga. There needs to be a fairer national approach that
enables safe, privacy-preserving access for New Zealand
researchers, so the benefits of AI in breast screening are
not captured mainly offshore.
“The clinical
implementation may be sensible. The data governance question
is the one we should not ignore.”
Conflict of
interest statement: “I work commercially in the
reproductive space in addition to my academic work, so
shouldn’t have any conflicts with this
statement.”
Ross Lawrenson, Professor of
Population Health, University of Waikato,
comments:
“It is good to see the Minister announce
investment in the use of AI to improve the efficiency and
effectiveness of our breast screening programme. New Zealand
has had a national mammography screening programme since
1998, and there has always been a challenge in balancing the
sensitivity and specificity of screening. In other words, we
do not want to miss cases of breast cancer, while at the
same time we want to avoid incorrectly labelling women as
having cancer when they do not. No screening system is 100%
sensitive and specific.
“When screening relies on
individual clinicians interpreting mammography images, we
know there is considerable variability in identifying
suspicious breast lumps that require biopsy. False-positive
rates, for example, can range from roughly 3% to more than
15%. To reduce this variability, BreastScreen Aotearoa
mandates double reporting of all mammograms. While this
improves consistency and diagnostic accuracy, it also
increases workforce demands and
costs.
“Computer-assisted diagnosis (CAD) has been
used to support mammogram interpretation for several
decades. More recently, the rapid expansion of AI
technologies in mammography has generated interest in their
potential to improve both the sensitivity and specificity of
the current double-reading system used by expert
radiologists.
“AI tools can assign risk scores to
breast lumps identified on mammography, categorising them as
higher or lower risk. These scores can assist radiologists
in clinical decision-making, including determining whether
follow-up imaging or biopsy is required. Current evidence
suggests that the improvements achieved with AI are modest
but meaningful. For example, one large study found that
implementing AI-assisted additional reading could detect an
additional 0.7–1.6 cancers per 1000 women
screened.
“However, AI systems are less accurate in
women with dense breast tissue. This highlights the
continuing importance of routinely recording breast density
and ensuring additional support and surveillance for
higher-risk women with dense breasts — an area that
remains a challenge for our screening system. There is
growing agreement that, particularly for lower-risk women,
AI-assisted diagnostics may safely replace the need for
double reading, helping to reduce pressure on radiology
services while maintaining screening
quality.”
Conflict of interest statement: “No
conflicts of
interest.”
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