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When Barzilay had a routine breast X-ray in her early 40s, the image showed a complex group of white spots in her breast tissue. The marks could be normal, or they could be cancerous-even the best doctors often struggle to tell the difference. Over the next two years Barzilay underwent a second X-ray, a MRI and a biopsy and she was finally diagnosed(诊断) with breast cancer in 2014.

Barzilay was treated and made a good recovery. But she remained terrified that the uncertainties of reading an X-ray could delay treatment so she made a career-changing decision.

A computer scientist at Massachusetts Institute of Technology, Barzilay had never studied health before. Her research used machine-learning techniques for natural language processing. But she had been looking for a new line of research and decided to team up with radiologists (放射科医生) to develop machine-learning algorithms (算法) that use computers' superior visual analysis to spot patterns in X-rays that the human eye might miss.

Over the next four years the team taught a computer program to analyze X-rays from about 32,000 women and told it which women had been diagnosed with cancer within five years of the scan.  They then tested the computer's matching abilities in 3,800 more patients. Their resulting algorithm, published last May in Radiology, was significantly more accurate at predicting cancer than practices generally used in clinics. When Barzilay's team ran the program on her own X-ray from 2012-one her doctor had cleared-the algorithm correctly predicted she was at a higher risk of developing breast cancer within five years than 98 percent of patients.

AI applications are entering clinics at a rapid rate, and physicians have met the technology with equal parts excitement about its potential to reduce their workload and fear about losing their jobs to machines. Algorithms also raise questions about how to regulate a machine that is constantly learning and changing and who is to blame if an algorithm gets a diagnosis wrong. Still, many physicians are excited about the promise of AI programs.

1.What advantage do Barzilay's algorithms take of computers to predict cancer?

A.Superior visual analysis.

B.Timely risk warning settings.

C.Natural-language processing techniques.

D.Large storage of radiological knowledge.

2.What does the underlined word "it" in Paragraph 4 refer to?

A.Cancer. B.Research.

C.The team. D.The program.

3.How do physicians react to AI applications in clinics?

A.They doubt the accuracy of the applications.

B.They have mixed feelings about the applications.

C.They promise to make the best of the applications.

D.They expect to rapidly popularize the applications.

4.It can be inferred from the text that

A.Barzilay suffered from breast cancer for two years in her forties

B.at first Barzilay didn't think X-ray was a reliable way of checking cancer

C.with Barzilay's algorithms her cancer could have been diagnosed earlier

D.Barzilay failed to turn to the best doctors to have her breast checked

高三英语阅读理解中等难度题

少年,再来一题如何?
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