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Google previously announced successful t...

    Google previously announced successful tests of machine learning systems designed to assist doctors. In one case, Google reported AI had examined eye diseases with equal accuracy to doctors. Other tests showed that machine learning can be used to study large amounts of patient data to predict future medical events.

Now the company has published two new studies showing a high level of success in identifying metastatic breast cancer. Metastatic means that cancer has spread from its main area to other parts of the body. Metastatic breast cancer is one of the deadliest, causing about 90 percent of all breast cancer deaths worldwide.

In metastatic breast cancer patients, the cancer often travels to nearby lymph nodes(淋巴结). Usually doctors examine lymph node tissue under a microscope to see whether cancer is present. Google notes that previous studies have shown that up to one-fourth of metastatic lymph node classifications end up being changed after a second examination. In addition, studies show that small metastatic material can be missed up to 67 percent of the time when examinations happen under extreme time restrictions.

Google says it created a mathematical algorithm(算法). The algorithm, called Lymph Node Assistant, is trained to find characteristics of tissue affected by metastatic cancer. When the system examined tissue images(图像), it was able to differentiate between metastatic cancer and non-cancer 99 percent of the time. In addition, the Lymph Node Assistant is highly effective at finding the positions of the cancers. Some of these positions would be too small for doctors themselves to identify. The research also showed that the algorithm method can reduce the usual time needed to examine the disease by about 50 percent.

But Google makes clear the AI-based system is not meant to replace the work of medical professionals. Instead, it is designed to reduce the number of false identifications and help doctors work faster and more effectively.

1.What is the main idea of Paragraph 1?

A.Google became a pioneer in training doctors.

B.Machine learning is able to stop future medical events.

C.Google developed artificial intelligence to help doctors.

D.Artificial intelligence cured eye diseases with equal accuracy to doctors.

2.What can we infer about metastatic breast cancer?

A.One-fourth of the metastatic breast cancer patients die in the end.

B.Metastatic breast cancer is very difficult to identify.

C.It results in 90 percent of deaths of all cancers.

D.It can be identified after a second examination.

3.What is the advantage of Google’s new mathematical algorithm?

A.It can offer effective treatment.

B.It can tell the exact positions of cancers

C.It costs 99 percent less time than before.

D.It improves the accuracy of identifying cancers by 50%.

4.What influence will the mathematical algorithm bring?

A.False identification of cancers will be avoided.

B.More effective prevention of cancers will be found.

C.The number of medical professionals will be reduced.

D.Doctors can have a faster understanding of patients’ condition.

 

1.C 2.B 3.B 4.D 【解析】 本文是一篇说明文,介绍了谷歌开发了人工智能来帮助医生更准确地识别转移性乳腺癌。 1.段落大意题。根据第一段内容,特别是Google previously announced successful tests of machine learning systems designed to assist doctors.可知,谷歌此前宣布成功测试了旨在帮助医生的机器学习系统。所以本段主要介绍了谷歌开发了人工智能来帮助医生,故选C。 2.推理判断题。根据第三段中的Google notes that previous studies have shown that up to one-fourth of metastatic lymph node classifications end up being changed after a second examination. In addition , studies show that small metastatic material can be missed up to 67 percent of the time when examinations happen under extreme time restrictions.可知,以前的研究表明,多达四分之一的转移性淋巴结分类在第二次检查后会改变,此外,研究表明,在极端的时间限制下进行检查时,小的转移性乳腺癌可以漏诊高达67%,也就是说转移性乳腺癌很难鉴别,故选B。 3.细节理解题。根据第四段中的In addition, the Lymph Node Assistant is highly effective at finding the positions of the cancers.可知,谷歌研发的新算法在发现癌变位置方面非常有效,由此可知,它的优点是能识别癌变的确切位置,故选B。 4.细节理解题。根据最后一段中的Instead, it is designed to reduce the number of false identifications and help doctors work faster and more effectively.可知,这种新算法旨在减少误诊的数量,帮助医生更快更有效地工作,由此可知,通过这种新算法,医生可以更快地了解病人的病情,故选D。
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