Sunday July 21, 2019

Artificial Intelligence Can Prove to be a Boon for Patients with Alzheimer’s

The findings demonstrated the potential valid clinical utility of “MemTrax”, administered as part of the online test in screening for variations in cognitive brain health

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A lady suffering from Alzheimer's. Flickr

Artificial Intelligence (AI) can prove to be essential for healthcare providers to detect and manage Alzheimer’s disease or a related form of dementia, from which 44 million people suffer worldwide.

In the study published in the Journal of Alzheimer’s Disease, the team introduced supervised Machine Learning (ML) as a modern approach and new value-added complementary tool in cognitive brain health assessment and related patient care and management.

With the increasingly favourable instrument “MemTrax” — an online memory test using image recognition — the clinical efficacy of this new approach as a memory function screening tool has been sufficiently demonstrated.

For the study, a team of researchers including from the Florida Atlantic University, SIVOTEC Analytics and Stanford University employed a novel application of supervised ML and predictive modeling to demonstrate and validate the cross-sectional utility of “MemTrax” as a clinical decision support screening tool for assessing cognitive impairment.

"The question for us now is not how to eliminate cholesterol from the brain, but about how to control cholesterol's role in Alzheimer's disease through the regulation of its interaction with amyloid-beta," Vendruscolo said.
In Alzheimer’s disease, patients start losing memory. Pixabay

The findings demonstrated the potential valid clinical utility of “MemTrax”, administered as part of the online test in screening for variations in cognitive brain health.

“Findings from our study provide an important step in advancing the approach for clinically managing a very complex condition like Alzheimer’s disease,” said lead author Michael F. Bergeron, Senior Vice President, SIVOTEC Analytics.

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“By analysing a wide array of attributes across multiple domains of the human system and functional behaviours of brain health, informed and strategically directed advanced data mining, supervised Machine Learning, and robust analytics can be integral for healthcare providers to detect and anticipate further progression in this disease and myriad other aspects of cognitive impairment,” he explained. (IANS)

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Researchers Develop AI-driven System to Curb ‘Deepfake’ Videos

Roy-Chowdhury, however, thinks we still have a long way to go before automated tools can detect “deepfake” videos in the wild

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Artificial Intelligence Bot
Artificial Intelligence Bot. Pixabay

At a time when “deepfake” videos become a new threat to users’ privacy, a team of Indian-origin researchers has developed Artificial Intelligence (AI)-driven deep neural network that can identify manipulated images at the pixel level with high precision.

Realistic videos that map the facial expressions of one person onto those of another — known as “deepfakes”, present a formidable political weapon in the hands of nation-state bad actors.

Led by Amit Roy-Chowdhury, professor of electrical and computer engineering at the University of California, Riverside, the team is currently working on still images but this can help them detect “deepfake” videos.

“We trained the system to distinguish between manipulated and nonmanipulated images and now if you give it a new image, it is able to provide a probability that that image is manipulated or not, and to localize the region of the image where the manipulation occurred,” said Roy-Chowdhury.

A deep neural network is what AI researchers call computer systems that have been trained to do specific tasks, in this case, recognize altered images.

These networks are organized in connected layers; “architecture” refers to the number of layers and structure of the connections between them.

While this might fool the naked eye, when examined pixel by pixel, the boundaries of the inserted object are different.

For example, they are often smoother than the natural objects.

artificial intelligence, nobel prize
“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society.” VOA

By detecting boundaries of inserted and removed objects, a computer should be able to identify altered images.

The researchers tested the neural network with a set of images it had never seen before, and it detected the altered ones most of the time. It even spotted the manipulated region.

“If you can understand the characteristics in a still image, in a video it’s basically just putting still images together one after another,” explained Roy-Chowdhury in a paper published in the journal IEEE Transactions on Image Processing.

“The more fundamental challenge is probably figuring out whether a frame in a video is manipulated or not”.

Also Read: TikTok Testing New Features Inspired by Instagram

Even a single manipulated frame would raise a red flag.

Roy-Chowdhury, however, thinks we still have a long way to go before automated tools can detect “deepfake” videos in the wild.

“This is kind of a cat and mouse game. This whole area of cybersecurity is in some ways trying to find better defense mechanisms, but then the attacker also finds better mechanisms.” (IANS)