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Twitter and social media platforms got me here: Donald Trump

It is because of Twitter and the social media platforms help him get around the media, that president Donald Trump has reached. The president accepted it

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Washington, March 22, 2017:  It is because of Twitter and the social media platforms help him get around the media, that president Donald Trump has reached. The president accepted it.

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“(I) probably wouldn’t be here right now, but very seldom. We have a tremendous group of people that listen and I can get around the media when the media doesn’t tell the truth, so I like that,” Trump told reporters at a joint White House news conference with visiting German Chancellor Angela Merkel.

Trump was responding to a question put up by a German reporter if he ever regretted his tweets.

“By the way, my second question, are there from time to time tweets that you regret,” a German reporter asked, as per PTI.

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Sharing the dais with Merkel, Trump stated that he and the German leader probably shared something when it came to the predecessor Obama Administration.

He was responding to a question pertaining to wiretapping.

“As far as wiretapping, I guess by this past administration, at least we have something in common, perhaps,” Trump said.

“And just to finish your question, we said nothing. All we did was quote a certain very talented legal mind who was the one responsible for saying that on television. I didn’t make an opinion on it,” Trump said.

– prepared by Sabhyata Badhwar of NewsGram. Twitter: @SabbyDarkhorse

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Facebook Aims to Make MRI Scans Faster Using AI With New York University

Advanced image reconstruction might enable ultra-low-dose CT scans suitable for vulnerable populations, such as pediatric patients, Facebook said

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Facebook partners with NYU to make MRI faster with AI. Pixabay

Facebook has forged a partnership with the New York University (NYU) on a research project that aims to make magnetic resonance imaging (MRI) scans up to 10 times faster by leveraging the power of Artificial Intelligence (AI).

If the project, called fastMRI, yields the desired results, it will make MRI technology available to more people, expanding access to this key diagnostic tool, Facebook said in a blog post on Monday.

MRI scanners provide doctors and patients with images that typically show a greater level of detail related to soft tissues — such as organs and blood vessels — than is captured by other forms of medical imaging.

But they are relatively slow, taking anywhere from 15 minutes to over an hour, compared with less than a second or up to a minute, respectively, for X-ray and CT scans.

These long scan times can make MRI machines challenging for young children, as well as for people who are claustrophobic or for whom lying down is painful.

Additionally, there are MRI shortages in many rural areas and in other countries with limited access, resulting in long scheduling backlogs.

Making MRI scanners faster has several benefits, including increased access to these devices for patients.

Sufficiently accelerated MRI devices could also reduce the amount of time patients must hold their breath during imaging of the heart, liver, or other organs in the abdomen and torso.

Increased speed could let MRI machines fill the role of X-ray and CT machines for some applications, allowing patients to avoid the ionising radiation associated with those scans.

MRI Scans
Making MRI scanners faster has several benefits, including increased access to these devices for patients. Pixabay

This NYU-Facebook project will initially focus on changing how MRI machines operate.

Currently, scanners work by gathering raw numerical data in a series of sequential views and turning the data into cross-sectional images of internal body structures that doctors then use to evaluate a patient’s health.

The larger the data set to be gathered, the longer the scan will take.

Using AI, it may be possible to capture less data and therefore scan faster, while preserving or even enhancing the rich information content of magnetic resonance images.

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The key is to train artificial neural networks to recognise the underlying structure of the images in order to fill in views omitted from the accelerated scan, Facebook said.

The Facebook Artificial Intelligence Research (FAIR) group, believes that though this project will initially focus on MRI technology, its long-term impact could extend to many other medical imaging applications.

For example, the improvements afforded by AI have the potential to revolutionise CT scans as well.

Advanced image reconstruction might enable ultra-low-dose CT scans suitable for vulnerable populations, such as pediatric patients, Facebook said. (IANS)