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Indian Railways to use artificial intelligence

Earlier, railways used a manual maintenance system

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Indian Railways is one of the most important and controversial transport in India. Wikimedia Commons
Indian Railways is one of the most important and controversial transport in India. Wikimedia Commons
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New Delhi. November 21, 2017:

Aiming to reduce the possibilities of signals failing, Indian Railways has undertaken remote condition monitoring of the system, a new approach for the national transporter, to predict failures through the effective use of Artificial Intelligence.

The Signalling system is vital for safe train operations and the railways completely depend on the health of its signalling assets along with real-time information.

Currently, the railways follow a manual maintenance system and adopt find-and-fix methods rather than predict-and-prevent approach.

“Now, we are introducing remote condition monitoring using non-intrusive sensors for continuous online monitoring of signals, track circuits, axle counters and their sub-systems of interlocking, power supply systems including the voltage and current levels, relays, timers,” said a senior Railway Ministry official involved with the project.

The system entails the collection of inputs on a pre-determined interval and sending this to a central location.

As a result, any flaws or problems in the signalling system would be detected on a real-time basis and rectified to avoid possible delays and mishaps.

The failure of signals is one of the major reasons for train accidents and delays.

Currently, remote monitoring of signalling is operational in Britain.

The system envisages data transfer through a wireless medium (3G, 4G and high-speed mobile) and data based on these inputs will be utilised, with help of Artificial Intelligence (AI), for predictive and prescriptive Big Data analytics.

This will enable prediction of signalling asset failures, automated self-correction and informed decisions on intervention strategies, said the official.

The railways have decided that trial is taken up in two sections of Western Railway and South Western Railway at Ahmedabad-Vadodara and Bengaluru-Mysuru.

Depending on the feedback, the system would gradually be extended to other sections. (IANS)

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Can Doctors Become Better With The Help Of Artificial Intelligence

The research now is on breast cancer, but doctors predict artificial intelligence will eventually make a difference in all forms of cancer and beyond.

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Liver Cancer, Cancer, Artificial Intelligece
A high-magnification image from a 2012 glioblastoma case is seen as an example in this College of American Pathologists image released from Northfield. VOA

Teacher Rishi Rawat has one student who is not human, but a machine.

Lessons take place at a lab inside the University of Southern California’s (USC) Clinical Science Center in Los Angeles, where Rawat teaches artificial intelligence, or AI.

To help the machine learn, Rawat feeds the computer samples of cancer cells.

“They’re like a computer brain, and you can put the data into them and they will learn the patterns and the pattern recognition that’s important to making decisions,” he explained.

AI may soon be a useful tool in health care and allow doctors to understand biology and diagnose disease in ways that were never humanly possible.

Cell Pattern, Artificial Intelligence
Artificial intelligence through machine learning can detect complex patterns in cell arrangement that would be difficult for humans to recognize. VOA

Doctors not going away

“Machines are not going to take the place of doctors. Computers will not treat patients, but they will help make certain decisions and look for things that the human brain can’t recognize these patterns by itself,” said David Agus, USC’s professor of medicine and biomedical engineering, director at the Lawrence J. Ellison Institute for Transformative Medicine, and director at the university’s Center for Applied Molecular Medicine.

Rawat is part of a team of interdisciplinary scientists at USC who are researching how Artificial Intelligence and machine learning can identify complex patterns in cells and more accurately identify specific types of breast cancer tumors.

Once a confirmed cancerous tumor is removed, doctors still have to treat the patient to reduce the risk of recurrence. The type of treatment depends on the type of cancer and whether the tumor is driven by estrogen. Currently, pathologists would take a thin piece of tissue, put it on a slide, and stain with color to better see the cells.

“What the pathologist has to do is to count what percentage of the cells are brown and what percentage are not,” said Dan Ruderman, a physicist who is also assistant professor of research medicine at USC.

health, artificial Intelligence
Health would also not predict wealth as effectively as it does overall adoption and future readiness. Pixabay

The process could take days or even longer. Scientists say artificial intelligence can do something better than just count cells. Through machine learning, it can recognize complicated patterns on how the cells are arranged, with the hope, in the near future of making a quick and more reliable diagnosis that is free of human error.

“Are they disordered? Are they in a regular spacing? What’s going on exactly with the arrangement of the cells in the tissue,” described Ruderman of the types of patterns a machine can detect.

“We could do this instantaneously for almost no cost in the developing world,” Agus said.

Computing power improves

Scientists say the time is ripe for the marriage between computer science and cancer research.

“All of a sudden, we have the computing power to really do it in real time. We have the ability of scanning a slide to high enough resolution so that the computer can see every little feature of the cancer. So it’s a convergence of technology. We couldn’t have done this, we didn’t have the computing power to do this several years ago,” Agus said.

Cell Pattern, artificial Intelligence
High resolution slide scanners plus stronger computer power allows for the possibility for AI to help doctors more accurately figure out the subtype of breast cancer a patient has. VOA

Data is key to having a machine effectively do its job in medicine.

“Once you start to pool together tens and hundreds of thousands of patients and that data, you can actually [have] remarkable new insight, and so AI and machine learning is allowing that. It’s enabling us to go to the next level in medicine and really take that art to new heights,” Agus said.

Also Read: Researchers Develop Nano Technology That Offers Hope For Better Cancer Testing

Back at the lab, Rawat is not only feeding the computer more cell samples, he also designs and writes code to ensure that the algorithm has the ability to learn features unique to cancer cells.

The research now is on breast cancer, but doctors predict artificial intelligence will eventually make a difference in all forms of cancer and beyond. (VOA)