Artificial Intelligence Better Than Humans at Detecting Breast Cancer
Artificial Intelligence Better Than Humans at Detecting Breast Cancer
(Dejan
Baric/Dreamstime.com)
Thursday, 02 January 2020 10:26 AM
A computer program can identify breast cancer from routine scans
with greater accuracy than human experts, researchers said in what they hoped
could prove a breakthrough in the fight against the global killer.
Breast cancer is one of the most common cancers in women, and
regular screening is vital in detecting the earliest signs of the disease in
patients who show no obvious symptoms.
In Britain, women over 50 are advised to get a mammogram every
three years, the results of which are analyzed by two independent
experts.
But interpreting the scans leaves room for error, and a small
percentage of all mammograms either return a false positive — misdiagnosing a
healthy patient as having cancer — or false negative — missing the disease as
it spreads.
Now researchers at Google Health have trained an artificial
intelligence model to detect cancer in breast scans from thousands of women in
Britain and the United States.
The images had already been reviewed by doctors in real life, but
unlike in a clinical setting the machine had no patient history to inform its
diagnoses.
The team found that their AI model could predict breast cancer
from the scans with a similar accuracy level to expert radiographers.
Further, the AI showed a reduction in the proportion of cases where
cancer was incorrectly identified — 5.7% in the U.S. and 1.2% in Britain,
respectively.
It also reduced the percentage of missed diagnoses by 9.4% among
U.S. patients and by 2.7% in Britain.
"The earlier you identify a breast cancer the better it is
for the patient," Dominic King, UK lead at Google Health, told AFP.
"We think about this technology in a way that supports and
enables an expert, or a patient ultimately, to get the best outcome from
whatever diagnostics they've had."
Computer 'second opinion'
In Britain, all mammograms are reviewed by two radiologists, a
necessary but labor-intensive process.
The team at Google Health also conducted experiments comparing the
computer's decision with that of the first human scan reader.
If the two diagnoses agreed, the case was marked as resolved. Only
with discordant outcomes was the machine then asked to compare with the second
reader's decision.
The study by King and his team, published in Nature, showed that
using AI to verify the first human expert reviewer's diagnosis could save up to
88% of the workload for the second clinician.
"Find me a country where you can find a nurse or doctor that
isn't busy," said King.
"There's the opportunity for this technology to support the
existing excellent service of the [human] reviewers."
The team said
further research was needed but they hoped that the technology could one day
act as a "second opinion" for cancer diagnoses.
© AFP/Relaxnews 2020
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