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AI to help in search for alien life

As life is currently known only to exist on Earth, the classification uses a "probability of life" metric which is based on the relatively well-understood atmospheric and orbital properties of the five target types

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There are many good uses of AI, but it can be misused too.
AI can now help astronomers find life on other planet. Pixabay
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  • AI can now help astronomers too
  • It can help them predict the probability of life on other planets
  • AI is being used in many things nowadays

Artificial Intelligence (AI) could help astronomers predict the probability of life on other planets, according to a new study. Using artificial neural networks (ANNs) researchers from Britain’s Plymouth University classified planets into five types, based on whether they are most like the present-day Earth, the early Earth, Mars, Venus or Saturn’s moon Titan, estimating a probability of life in each case.

All five of these objects are rocky bodies known to have atmospheres and are among the most potentially habitable objects in the Solar System.

Alien
Digital Imaginary Representation of Extraterrestrial beings. Wikimedia commons

“We’re currently interested in these ANNs for prioritising exploration for a hypothetical, intelligent, interstellar spacecraft scanning an exoplanet system at range,” said Christopher Bishop from the varsity.

“We’re also looking at the use of large area, deployable, planar Fresnel antennas to get data back to Earth from an interstellar probe at large distances. This would be needed if the technology is used in robotic spacecraft in the future,” Bishop added.

Also Read: Analysis of Ancient Aliens show on History Channel

ANNs are systems that attempt to replicate the way the human brain learns. Atmospheric observations — known as spectra — of the five Solar System bodies are presented as inputs to the network, which is then asked to classify them in terms of the planetary type. As life is currently known only to exist on Earth, the classification uses a “probability of life” metric which is based on the relatively well-understood atmospheric and orbital properties of the five target types.

Aliens may or may not exist, the question remains. Pixabay

“Given the results so far, this method may prove to be extremely useful for categorising different types of exoplanets using results from ground-based and near-Earth observatories,” said Angelo Cangelosi, the supervisor of the project.

The technique may also be ideally suited to selecting targets for future observations, given the increase in spectral detail expected from upcoming space missions such European Space Agency’s Ariel Space Mission and NASA’s James Webb Space Telescope. The work was presented at the European Week of Astronomy and Space Science (EWASS) in Liverpool. 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)