题目内容：

AI can identify rare genetic disorders

People with genetic syndromes (基因遗传综合症) sometimes have revealing facial features, but using them to make a quick and cheap diagnosis can be tricky when there are hundreds of possible conditions they may have. A new neural(神经的) network that analyses photographs of faces can help doctors narrow down the possibilities.

Gurovich at biotechnology firm FDNA in Boston and his team built a neural network to look at the gestalt (形态)– or overall impression of faces and return a list of the 10 genetic syndromes a person is most likely to have.

They trained the neural network, called DeepGestalt, on 17,000 images correctly labeled to correspond to more than 200 genetic syndromes. The team then asked the AI to identify potential genetic disorders from a further 502 photographs of people with such conditions. It included the correct answer among its list of 10 responses 91 per cent of the time.

Gurovich and his team also tested the AI’s ability to distinguish between different genetic mutations (突变) that can lead to the same syndrome. They used images of people with Noonan syndrome, which can result from mutations in one of five genes. DeepGestalt accurately identified the genetic source of the physical appearance 64 per cent of the time.

“It’s clearly not perfect,” says Gurovich. “But it’s still much better than humans are at trying to do this.”

As the system makes its assessments, the facial regions that were most helpful in the determination are highlighted and made available for doctors to view. This helps them to understand the relationships between genetic make-up and physical appearance.

The fact that the diagnosis is based on a simple photograph raises questions of privacy. If faces can reveal details about genetics, then employers and insurance providers could, in principle, secretly use such techniques to discriminate against people with a high probability of having certain disorders.

However, Gurovich says the tool will only be available to doctors. Christoffer Nellaker at the University of Oxford says this technique could bring significant benefits for those with genetic syndromes.

“This is not fundamentally different information than we’re sharing walking down the street, or we’re happy to share with Facebook or Google,” he says. “But questioning the data in this way means you can obtain information about health or disease status.

“The real value here is that for some of these extreme rare diseases, the process of diagnosis can be many, many years. This kind of technology can help narrow down the search space and then be confirmed through checking genetic markers,” he says.

For some diseases, this kind of technology will cut down the time to diagnose thoroughly. For others, it could perhaps add a means of finding other people with the disease and, in turn, help find new treatments or cures.

1.What is the purpose of Gurovich’s neural network?

A.To test the AI’s ability.

B.To analyze photographs of faces.

C.To help doctors reduce the range of the diagnosis.

D.To research the overall impression of patients’ faces.

2.What disadvantage does Deep Gestalt bring?

A.It will probably involve in the people’s privacy.

B.It cannot provide information about health or disease.

C.The diagnosis based on a simple photograph is not accurate.

D.It could perhaps add a means of finding other people with the disease.

3.What can we learn from the passage?

A.The result of the assessments for this system is perfect.

B.Deep Gestalt can correctly label 200 genetic syndromes.

C.It seems doubtful to use AI to distinguish genetic mutations.

D.This kind of technology can speed up the diagnostic process.

4.What is the author’s attitude to this technique?

A.Supportive. B.Puzzled.

C.Doubtful. D.Negative.