In the late 20 pregnancy was normal, simple birth But after a few months, some problems appear. The child had an infection of the ear after ear infection and difficulty breathing at night. He was small for his age, and his fifth birthday, still has not spoken. It started with cramps. MRI brain, molecular analyzes, basic genetic testing, dozens of doctors; Nothing was answered. Without other options, in 2015 his family decided to sequence their portion of exomes from the genome that codes for proteins - to see if he had inherited a genetic disease from their parents. A variant has shown: ARID1B.
Now ther is an application called Face2Gene. The application, developed by programmers who got Facebook to see your face in the photos of your friends performs millions of small projections in quick succession, how much angle of the eye? How narrow is the crack in the eyelid? How low are your ears? Quantified calculated, and ranks to suggest the most likely syndromes associated with facial phenotype. There is also an overlay image of the heat map that shows what are the most indicative match features.
Face2Gene benefits from the fact that so many genetic conditions have a "face" revealing - the unique constellation of characteristics that can provide clues to a potential diagnosis. It is just one of several new technologies that use the speed of modern computers can analyze, sort and find the pattern of huge amounts of data. They are built in the fields of artificial intelligence called in-depth learning and neural networks among the most promising to deliver 50 years Amnesty International's promise to revolutionize medicine by recognizing and diagnosing the disease.
Genetic syndromes are not the only diseases that can be helped by learning the machine. The Autism Test RightEye GeoPref can detect the early stages of autism in children as young as 12 months in crucial steps where early intervention can make a big difference. Unveiled on January 2 at the Las Vegas CES, using infrared sensor technology to test the baby's eye movements as they watch a split video screen: one side is filled with people and faces, the other with the displacement of geometric shapes. Children of this age should be much more interested in faces than abstract objects, so the time they look at each screen to indicate where the child of the autistic spectrum may fall.
In the validation studies carried out by the inventor of the test, UC San Diego researcher Karen Pierce, a test correctly predicted autism with 86 percent of the time in more than 400 infants. That said, it is still fairly new, and has not yet been approved by the FDA as a diagnostic tool. "Regarding learning machine, it is the easiest test we have," says research director of RightEye Melissa Hunfalvay. "But before that, he was only a doctor or parent observations that can lead To a diagnosis. And the problem with which it was measurable. "
A similar tool can help in the early detection of America's sixth leading cause of death: Alzheimer's disease. Often doctors do not recognize the physical symptoms in time to try any of the disease, existing measures. However, learning machine hear what doctors can not: proof of cognitive impairment in speech. This is the Toronto-based Winter Light Labs develops a tool for taking dementia notes at an early stage. Co-founder Frank Rudzicz call these clues "floating" and "shimmering" high-frequency waves only computers, not humans, can hear.
Winter Light utility is much more sensitive than the pen and paper tests doctors currently use to evaluate Alzheimer's disease. In addition to being raw data-wise, these tests can not be taken more than once every six months. Rudzicz tool can be used several times a week, which means that it gets good days, bad days, and measure the cognitive functions of a patient over time. The product is still in beta, but is currently controlled by healthcare professionals in Canada, the United States and France.
If this all feels a bit scary science fiction to you, it's good to remember that doctors have to rely on computers with your diagnosis for a long time. Indeed, machines are very sensitive to both detect and analyze the many subtle signs that our bodies are behaving badly. For example, without a computer, the number two patient would never have been able to compare their thousands of other exome, and find him scoring with the Coffin-Siris syndrome gene mutation.
But nothing that makes doctors out of date. Even Face2Gene-which according to its inventor can diagnose up to half of the known 8,000 genetic syndrome using facial motifs gleaned from hundreds of thousands of images in its database needs a doctor (such as Karen Gripp ) With sufficient experience to verify the results. In this way, machines are an extension of what medicine has always been: a science that develops more powerful with each new data point.
Source:-www.wired.com
0 Comments