For all our efforts to
control malaria, diagnosing it in many parts of the world still requires
counting malaria parasites under the microscope on a glass slide
smeared with blood. Now an artificial intelligence program can do it
more reliably than most humans.
That AI comes inside an automated microscope called the
Autoscope, which is 90 percent accurate and specific at detecting
malaria parasites. Charles Delahunt and colleagues at Intellectual
Ventures Laboratory—the research arm of Nathan Myhrvold’s patent
licensing company Intellectual Ventures in Seattle—built the system with
support from Bill and Melinda Gates through the Global Good Fund. The
Autoscope was tested in the field at the Shoklo Malaria Research Unit on the Thailand-Myanmar border during malaria season in December 2014 and January 2015. The results were published in December.
The Autoscope, a 15-inch-tall, 7-inch-wide smooth white
box enclosing a microscope with an attached laptop running a software
algorithm, uses deep learning
to analyze microscope images. Deep-learning software uses artificial
neural networks mimicking the brain to allow computers to recognize
abstract patterns. Delahunt’s team trained the software on 120 slides
from collections around the world, both with and without malaria. The
software uses visual features like shape, color, and texture to
calculate the probability that a given object is a malaria parasite. It
classified 170 samples during the field testing in Thailand.
"It could have broad applicability, not only in
research and surveillance of antimalarial drug resistance but also in
clinical practice,” says Mehul Dhorda, head of the Asia Regional Centre
at the WorldWide Antimalarial Resistance Network. Dhorda works with
Intellectual Ventures on some of the current Autoscope trials but was
not an author of the research. The Autoscope uses deep-learning software to quantify the malaria parasites in a sample.
In 2015, malaria affected 214 million people and killed
an estimated 438,000. Worldwide, we spend about $2.7 billion a year on
fighting and controlling malaria.
Current diagnosis of malaria relies on two approaches:
microscopy and rapid diagnostic tests. Rapid diagnostic tests are
portable cards that display bands in the presence of malaria, much like
an at-home pregnancy test. They’re inexpensive, but even a small cost
can be prohibitive. By contrast, once a clinic has a microscope and some
glass slides, they can be reused indefinitely without further costs.
Another disadvantage of rapid diagnostic tests is that
they don’t quantify malaria. They only detect its presence or absence,
so they are not ideal for cases of drug-resistant or severe malaria. “If
you have a severely ill child with severe malaria, then it's important
that you control the parasite density. Every six hours you want to see,
is it coming down? Is my treatment having an effect?” says Albert Kilian,
a public health and malaria expert at Tropical Health consultancy. “And
in these cases, [rapid diagnostic tests] don't serve, so you need to
count [the parasites].”
The microscopy currently used to quantify the parasites
requires well-trained microscopists, and many malaria-prone areas don’t
have enough of those, or the resources to train new ones. By contrast,
anyone can use the Autoscope. “We’re not as good as the very best
humans, but we’re certainly better than almost all microscopists in the
field,” according to the World Health Organization’s standards, says
Delahunt.
There are obstacles to overcome before the Autoscope
can be used where it’s needed most. The device requires electricity, so
it’s useless in areas that lack adequate power.
And then there is the cost issue. Intellectual Ventures
Laboratory is currently looking for a commercial partner to help it
drive down the cost of the Autoscope to $1,500 to $4,000. It also plans
to spend 2016 testing the Autoscope in more field trials in Peru and
Southeast Asia, including some tests for drug-resistant malaria cases.
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