Thursday July 18, 2019

Scientists in Australia Use Artificial Intelligence to Develop New Vaccine Against the Flu

The key to the technology are adjuvants, which are substances that help existing therapies work better to prevent infection

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artificial intelligence, drugs
FILE - Ami-Louise Cochrane, center, receives a flu vaccination at Flinders Medical Center, in Adelaide, Australia. VOA

Scientists in Australia say they have used artificial intelligence to develop a powerful new vaccine against the flu. The team from Flinders University believe it is the first time a computer has used its own machine learning to design a new drug for use in people.

The computer’s name is Sam, or Search Algorithm for Ligands, and Australian researchers say its new flu drug is a “turbo-charged” version of existing treatments.  The key to the technology are adjuvants, which are substances that help existing therapies work better to prevent infection.

The artificial intelligence program was fed information on influenza vaccines that work as well as those that do not, and left to its own devices without any help from scientists at Flinders University.  They say it is a start of a “new era” in artificial intelligence research.

Artificial intelligence
The team from Flinders University believe it is the first time a computer has used its own machine learning to design a new drug for use in people. Pixabay

“We took existing drugs that we know work.  We took examples of drugs that do not work, or have failed and we essentially showed all of that to the A.I. program called Sam,” explains Dr. Nikolai Petrovsky, from Flinders University in Adelaide. “[It] came up with its own suggestion of what might be an effective adjuvant, which we then took and tested, and, sure enough, it worked.”

ALSO READ: Researchers Develop Artificial Intelligence Method that can Help Crops Cope with Climate Changes

A clinical trial will soon start on 240 volunteers in the United States.  It is sponsored by the National Institute of Allergy and Infectious Diseases, part of the U.S. National Institutes of Health.

The World Health Organization has said the 2019 influenza season appeared to have started earlier than previous years in Australia, Chile, South Africa and New Zealand.  The disease kills many thousands of people around the world each year. More than 115,000 influenza cases have been reported in Australia and authorities say 226 people have died so far this year. (VOA)

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Artificial Intelligence to Play a Critical Role in Diagnosing Breast Cancer Quickly

"We had about 80 per cent accuracy rate. We will continue to refine the algorithm by using more real-world images as inputs,” Oberai said

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Cancer, Patients, Invasive
The treatments kill healthy cells as well as cancerous ones, and the side effects are legendary. Pixabay

Breast ultrasound elastography is an emerging imaging technique that provides information about a potential breast lesion and researchers have identified the critical role AI can play in making this technique more efficient and accurate.

Using more precise information about the characteristics of a cancerous versus non-cancerous breast lesion, this methodology using Artificial Intelligence (AI) has demonstrated more accuracy compared to traditional modes of imaging.

In the study published in the journal Computer Methods in Applied Mechanics and Engineering, Indian-origin researchers Dhruv Patel and Assad Oberai from the University of Southern California showed that it is possible to train a machine to interpret real-world images using synthetic data and streamline the steps to diagnosis.

In the case of breast ultrasound elastography, once an image of the affected area is taken, it is analysed to determine displacements inside the tissue. Using this data and the physical laws of mechanics, the spatial distribution of mechanical properties, like its stiffness, is determined.

In the study, researchers sought to determine if they could skip the most complicated steps of this workflow.

Cancer
Cancer Ribbon. Pixabay

For this, the researchers used about 12,000 synthetic images to train their Machine Learning algorithm. This process was similar to how photo identification software works, i.e learning through repeated inputs on how to recognize a particular person in an image, or how our brain learns to classify a cat versus a dog.

Through enough examples, the algorithm was able to glean different features inherent to a benign tumour versus a malignant tumour and make the correct determination.

Also Read- Over 16 Million Accounts of Indian Influencers on Instagram are Fake

The researchers achieved nearly 100 per cent classification accuracy on synthetic images. Once the algorithm was trained, they tested it on real-world images to determine how accurate it could be in providing a diagnosis, measuring these results against biopsy-confirmed diagnoses associated with these images.

“We had about 80 per cent accuracy rate. We will continue to refine the algorithm by using more real-world images as inputs,” Oberai said. (IANS)