The world of social media is not just selfies and pompous statuses. It’s much more than that. The second installment of ‘ Kolkata Adibasi Facebook Meet’ to be held at the Victoria Memorial Hall grounds is an example.
Around 642 Facebook users belonging to the ‘ educated and privileged’ section of West Bengal’s adivasi community have been invited for the event. The meet aims to increase unity in the community and hold positive discussion on how to harness social media for tribal development.
“We are trying to translate the virtual friendship into real bonding so that this platform can be used to promote development and unity among the tribal members,” Pradip Kumar Hansda, one of the organizers, told a news agency.
He said that the social media platform is the perfect place for the better off members to take up problems facing their community and provide solutions.
“Most of the people are from Bengal tribes such as Santals and their clans like Murmu, Soren etc. We have members of the tribe from neighbouring states of Odisha and Bihar as well. There are tribes from other parts of India too. We have started with Bengal and we want to take it to the national level,” Hansda said.
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.
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.
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)