Gizmorama - August 22, 2018
An AI system has been created that can identify neurological illnesses in CT scans in mere seconds. That's incredible!
Learn about this and more interesting stories from the scientific community in today's issue.
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* New AI system can screen for neurological illnesses in seconds *
Researchers have developed an artificial intelligence method that can identify a range of acute neurological illnesses in CT scans within a few seconds, when time is essential in assessing the life-threatening conditions.
Conditions such as stroke, hemorrhage and hydrocephalus were identified much faster with deep learning than through human diagnosis, according to a study conducted at the Icahn School of Medicine at Mount Sinai and published Monday in the journal Nature Medicine.
"With a total processing and interpretation time of 1.2 seconds, such a triage system can alert physicians to a critical finding that may otherwise remain in a queue for minutes to hours," senior author Dr. Eric Oermann, an instructor in the Department of Neurosurgery at Mount Sinai, said in a press release. "We're executing on the vision to develop artificial intelligence in medicine that will solve clinical problems and improve patient care."
The Mount Sinai AI Consortium, known as "AISINAI," first developed first AI method to assess the neurological illnesses. The consortium is a group of scientists, physicians and researchers dedicated to developing artificial intelligence for practical uses in medicine.
"The application of deep learning and computer vision techniques to radiological imaging is a clear imperative for 21st century medical care," said study author Dr. Burton Drayer, chairman of radiology at the Mount Sinai Health System.
Researchers programmed the AI system by using 37,236 head CT scans to identify whether an image contained critical or non-critical findings. It used "weakly supervised learning approaches" using natural language processing and large clinical datasets from the Mount Sinai Health System.
In all, 96,303 reports were analyzed. Images marked urgent -- or STAT -- took an average time of 174 minutes from when the test was ordered until a preliminary report is published, while routine ones took 241 minutes among radiologists. That includes the gap between after the test and when a radiologist looks at the scans.
The computer software was tested for how quickly it could recognize and provide notification compared with the time it took a radiologist to determine a disease.
It took the physician 150 times longer -- three minutes -- to assess the image.
Within the next two years, the researchers expect to have enhanced computer labeling of CT scans and a shift to "strongly supervised learning approaches" and novel techniques for increasing data efficiency.
"The expression 'time is brain' signifies that rapid response is critical in the treatment of acute neurological illnesses, so any tools that decrease time to diagnosis may lead to improved patient outcomes," study co-author Dr. Joshua Bederson, chairman for the Department of Neurosurgery at Mount Sinai.
*-- Physicists improve simulations of quantum particles, systems --*
Physicists have developed a more sophisticated and accurate way to simulate quantum particles and quantum systems. The breakthrough could speed up the development of quantum technologies.
Quantum physics, or quantum theory, is the study of the behavior of individual subatomic particles. The study of quantum mechanics has revealed the tremendous computation potential of qubits, or quantum bits, the smallest unit of quantum information.
Unlike classical bits, the binary backbone of classical computer technologies, which can represent either zero or one, quantum bits can represent both zero and one simultaneously in a state of superposition.
Simulations suggest quantum bits can be used to perform computation tasks at faster speeds and with greater efficiency than classical supercomputers.
But while lab experiments have shown the storage and manipulation of quantum information is possible, producing working quantum computers has proven much more difficult than simulations suggested. According to a new study, published Monday in the journal Nature Communications, that's because quantum simulations are inexact.
In reality, qubits don't behave like simple simulated qubits. They're not isolated. Quantum particles are continuously interacting with a near-infinite number of other particles. Replicating this reality via mathematics is extremely difficult.
The latest research promises to improve the ability of quantum simulations to account for the relationships between qubits and surrounding particles. By making quantum simulations more accurate and realistic, scientists hope to inspire new insights into quantum mechanics and perhaps pave the way for the next quantum computer.
"Our research has found a ground-breaking new way of keeping the most relevant fraction of information, allowing an exact description of the behavior of the qubit, even on a regular laptop," Brendon Lovett, theoretical physicist at the University of St. Andrews, said in a news release. "This work not only opens up the possibility of more faithful simulations of the next generation of quantum processors but could allow us whole new insights into how quantum mechanics works when many particles are put together."
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