Tuesday July 23, 2019
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Google Street Powers Artificial Intelligence Tool to Supervise Road Infrastructure

The fully-automated system is based on AI-powered object detection to identify street signs in the freely available images

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In this method, instructions are given to the companies staff members to perform transactions such as money transfers, as well as malicious activity on the company's network. Pixabay

By tapping into Google Street View images, researchers have developed a new programme using artificial intelligence (AI) to monitor the stop and give way (yield) signs needing replacement or repair. The fully-automated system is based on AI-powered object detection to identify street signs in the freely available images.

Published in the journal of Computers, Environment and Urban Systems, the study shows the system detects signs with near 96 per cent accuracy, identifies their type with near 98 per cent accuracy and can record their precise geo-location from the 2D images.

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File:Opel Astra Google Street View. Wikimedia Commons

“The proof-of-concept model was trained to see ‘stop’ and ‘give way’ (yield) signs, but could be trained to identify many other inputs and was easily scalable for use by local governments and traffic authorities,” said the study lead author Andrew Campbell from RMIT University in Australia.

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Municipal authorities spend a large amount of time and money monitoring and recording the geo-location of traffic infrastructure manually, a task which also exposes workers to unnecessary traffic risks. “By using free and open source tools, we’ve developed a fully automated system for doing that job, and doing it more accurately,” Campbell said. (IANS)

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Researchers Develop Artificial Intelligence Tool in Chest X-Rays to Predict Long Term Mortality

Each image was paired with a key piece of data: Did the person die over a 12-year period?

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artificial intelligence
The goal was for CXR-risk to learn the features or combinations of features on a chest X-ray image that best predict health and mortality. Pixabay

Researchers have developed an Artificial Intelligence (AI)-powered tool that can harvest information in chest X-rays to predict long-term mortality.

The findings of this study, published in the journal JAMA Network Open, could help to identify patients most likely to benefit from screening and preventive medicine for heart disease, lung cancer and other conditions.

“This is a new way to extract prognostic information from everyday diagnostic tests,” said one of the researchers, Michael Lu, from Massachusetts General Hospital (MGH) of Harvard Medical School. “It’s information that’s already there that we’re not using, that could improve people’s health,” Lu said. Lu and his colleagues developed a convolutional neural network – an AI tool for analysing visual information – called CXR-risk.

artificial Intelligence
Next, Lu and colleagues tested CXR-risk using chest X-rays for 16,000 patients from two earlier clinical trials. Pixabay

It was trained by having the network analyse more than 85,000 chest X-rays from 42,000 participants who took part in an earlier clinical trial. Each image was paired with a key piece of data: Did the person die over a 12-year period? The goal was for CXR-risk to learn the features or combinations of features on a chest X-ray image that best predict health and mortality.

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Next, Lu and colleagues tested CXR-risk using chest X-rays for 16,000 patients from two earlier clinical trials. They found that 53 per cent of people the neural network identified as “very high risk” died over 12 years, compared to fewer than four per cent of those that CXR-risk labeled as “very low risk.”

The study found that CXR-risk provided information that predicts long-term mortality, independent of radiologists’ readings of the x-rays and other factors, such as age and smoking status. Lu believes this new tool will be even more accurate when combined with other risk factors, such as genetics and smoking status. (IANS)