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X-rays using AI could reduce waiting times for expert diagnosis from 11 days to less than THREE
- Intelligent X-rays would be able to spot chest abnormalities independently
- He would report any problems and refer them urgently to a radiologist for diagnosis.
- Computer Vision and Machine Learning Accelerate Anomaly Identification
By Joe Pinkstone for Mailonline
published: 19h02, 21st January 2019 | Update: 7:12 pm EST, January 21, 2019
New studies show that the X-ray devices of the future will be powered by artificial intelligence (AI) in order to ease the burden of doctors and detect chest abnormalities.
The software uses computer vision and machine learning to speed up the identification of abnormalities and directs them accordingly to a human specialist.
It is thought that the system, should it be implemented, could reduce the time required to receive the opinion of an expert radiologist from 11 days to less than three.
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New studies show that the X-ray devices of the future will be powered by artificial intelligence (AI) in order to ease the burden of doctors and detect chest abnormalities. It is thought that the system, should it be implemented, could reduce the time required to receive the opinion of an expert radiologist from 11 days to less than three (stock)
The study, conducted at the University of Warwick, also involved an algorithm capable of reading radiology reports, understanding the results and the priority level of the exam.
The research, which was conducted in collaboration with Guy's and the NHS Foundation Trust in St Thomas, London, was published in the journal Radiology.
The researchers showed the machine more than 500,000 anonymized X-rays to form their AI.
They claim that this allowed him to learn visual models and then link him to a corresponding emergency level.
The researchers showed the machine more than 500,000 anonymized X-rays to form their AI. They claim that this allowed him to learn visual models and then link him to a corresponding emergency level (stock)
WHAT IS AN X-RAY?
An X-ray is a painless procedure that produces images of the body's interior to detect a range of conditions.
It causes a type of radiation through the body, which is then absorbed at different speeds by different parts of the body.
A detector that captures x-rays after their pbadage and transforms them into an image.
The dense parts of the body that X-rays have difficulty in crossing, such as bones, appear in clear white.
The milder parts, like the heart and lungs, appear darker.
X-rays can be used to detect fractures, dental problems, tumors and lung or heart problems, to name a few.
Many people are afraid to be exposed to radiation during an x-ray. However, the part of the body to be examined is only exposed for a fraction of a second.
The amount of radiation used is generally a few days to a few years of the amount naturally released by the environment.
It is thought that the risk of cancer is very low.
Source: NHS choice
Professor Giovanni Montana, head of the research team and president of data science at the WMG of the University of Warwick, said, "Imaging reports based on artificial intelligence could be a valuable tool for improving the workflow of departments and the efficiency of the workforce.
"Increasing clinical demands on radiology departments around the world have challenged current models of service delivery, particularly in publicly funded health systems.
"It is now impossible for many radiology departments with their current workforce to report all acquired x-rays in a timely manner, resulting in a significant backlog of studies late.
"In the UK, it is estimated that at any given time more than 300,000 x-rays are waiting more than 30 days for the notification.
"The results of this research show that other models of care, such as computer vision algorithms, could be used to significantly reduce delays in the process of identifying and treating abnormal X-rays – especially for thoracic radiographs, which account for 40% of cases. all diagnostic images made around the world.
"The application of these technologies also extends to many other imaging modalities, including MRI and CT."
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