Artificial intelligence (AI) technology may soon be a useful tool for doctors. It may help them better understand and treat diseases like breast cancer in ways that were never before possible.
Rishi Rawat teaches AI at the University of Southern California’s (USC) Clinical Science Center in Los Angeles. He is part of a team of scientists who are researching how AI and machine learning can more easily recognize cancerous growths in the breast. Rawat provides information about cancer cells to a computer. He says this data helps the machine learn. “. . . You can put the data into computers and they will learn the patterns and the pattern recognition is important to making decisions.”
David Agus is another USC researcher. He says machines are not going to take the place of doctors. “Computers will not treat patients, but they will help make certain decisions and look for things that the human brain can’t recognize by itself. Once a confirmed cancerous growth is removed, doctors still have to treat the patient to reduce the risk of cancer returning. The form of treatment depends on the kind of cancer.”
Currently, researchers take a thin piece of tissue, put it on a small piece of glass and add color to better see the cells. That process could take days or even longer. Scientists say artificial intelligence can do something better than just count cells. Through machine learning, it can recognize complex patterns, or structures, and learn how the cells are organized.
The hope is that machines will soon be able to make a quick identification of cancer that is free of human mistakes. “All of a sudden, we have the computing power to really do it in real time. . . We couldn’t have done this, we didn’t have the computing power to do this several years ago, but now it’s all changed.” Agus adds that the process could be done for almost no cost in the developing world. He says that having a large amount of information about patients is important for a machine to effectively do its job in medicine.
The University of Southern California researchers are now only studying breast cancer. But doctors predict artificial intelligence will one day make a difference in all forms of cancer.
1.In Rishi Rawat’s research, ________.
A.the data put into computers contributes to cancer recognition
B.many cancers are being studied at the moment
C.machine learning has replaced doctors’ work
D.the focus is on the cure for cancer
2.David Agus’s words in Paragraph 3 are used to ________.
A.provide some advice for doctors B.introduce the development of cancer
C.appeal to scientists to research into cancer D.explain the function of AI in treating cancer
3.What can we infer from the text ?
A.AI can make decisions for doctors.
B.Developing countries might be lack of funds.
C.AI will hopefully make an accurate identification of cancer.
D.Computing power has long helped with the identification of cancer.
4.What is the author’s attitude towards AI used in treating cancer?
A.Positive. B.Indifferent. C.Doubtful. D.Negative.
1.A; 2.D; 3.C; 4.A
解析:1.题干的意思是在Rishi Rawat的研究中,_____。根据文章第二段提到“He is part of a team of scientists who are researching how AI and machine learning can more easily recognize cancerous growths in the breast. Rawat provides information about cancer cells to a computer. He says this data helps the machine learn.(他是研究人工智能和机器学习如何更容易识别乳腺癌变的科学家团队的一员。Rawat向计算机提供有关癌细胞的信息。他说这些数据帮助机器学习。)”可知,在Rishi Rawat的研究中,输入电脑的数据有助于癌症的识别。结合选项,A项输入电脑的数据有助于癌症的识别;B项目前正在研究许多癌症;C项机器学习已经取代了医生的工作;D项重点是癌症的治疗。可知本题答案为A。
2.题干的意思是大卫·阿古斯在第3段中的话是用来_____。根据文章第三段大卫·阿古斯说的话提到“Computers will not treat patients, but they will help make certain decisions and look for things that the human brain can't recognize by itself.(计算机不会治疗病人,但它们将帮助做出某些决定,并寻找人类大脑无法自己识别的东西。)”可知,大卫·阿古斯在第3段中的话是用来解释人工智能在治疗癌症中的作用。结合选项,A项为医生提供一些建议;B项介绍癌症的发展;C项呼吁科学家研究癌症;D项解释人工智能在治疗癌症中的作用。可知本题答案为D。
3.题干的意思是我们能从文本中推断出什么?A项人工智能可以为医生做决定;B项发展中国家可能缺乏资金;C项人工智能有望准确识别癌症;D项长期以来,计算能力一直有助于癌症的识别。根据文章第三段提到“He says machines are not going to take the place of doctors. Computers will not treat patients, but they will help make certain decisions and look for things that the human brain can't recognize by itself.(他说,机器不会取代医生。计算机不会治疗病人,但它们将帮助做出某些决定,并寻找人类大脑无法自己识别的东西。)”可知,人工智能是帮助起到辅助的作用,而不会为医生做决定,故A项错误。根据文章第五段提到“Agus adds that the process could be done for almost no cost in the developing world.(Agus补充说,在发展中国家,这一过程几乎不需要任何成本。)”可知,发展中国家并不会有缺乏资金的问题,故B项错误。根据文章最后一段提到“But doctors predict artificial intelligence will one day make a difference in all forms of cancer.(但医生预测,人工智能终有一天会在所有癌症中发挥作用。)”以及前文的内容可知,人工智能有望准确识别癌症,故C项正确。根据文章第五段提到“We couldn't have done this, we didn’t have the computing power to do this several years ago, but now it's all changed.(我们不可能做到这一点,几年前我们没有计算能力做到这一点,但现在一切都改变了。)”可知,计算能力并不是在长期以来一直有助于癌症的识别,而是现在才能做到,故D项错误。结合选项,可知本题答案为C。
4.题干的意思是作者对人工智能治疗癌症的态度是什么?根据文章第五段提到“The hope is that machines will soon be able to make a quick identification of cancer that is free of human mistakes.(希望机器很快就能快速识别出没有人为错误的癌症。)”可知,作者对人工智能治疗癌症的态度是积极的。结合选项,A项积极的;B项冷淡的;C项怀疑的;D项消极的。可知本题答案为A。
科教类阅读的概念:
科教类阅读主要考查考生对书面语篇的整体领悟能力和接受及处理具体信息的能力。试题的取材,密切联系当前我国和世界经济、科技等方面的变化,有关数据的来源真实可信。
科教类文章阅读技巧:
一、材料特点:
这类文章的总体特点是:科技词汇多,句子结构复杂,理论性强,逻辑严谨。具体说来它有以下几个特点:
1、文章中词汇的意义比较单一、稳定、简明,不带感情色彩,具有单一性和准确性的特点。这类文章通常不会出现文学英语中采用的排比、比喻、夸张等修辞手法,一词多义的现象也不多见。
2、句子结构较复杂,语法分析较困难。为了描述一个客观事物,严密地表达自己的思想,作者经常会使用集多种语法现象于一体的长句。
3、常使用被动语态,尤其是一些惯用被动句式。
二、命题特点:
科普类阅读的主要命题形式有事实细节题、词义猜测题、推理判断题以及主旨概括题等,其中推理判断题居多。
三、应对策略:
1、要想做好科普英语阅读理解题,同学们就要注意平时多读科普知识类文章,学习科普知识,积累常见的科普词汇,从根本上提高科普英语的阅读能力。
2、要熟悉科普类文章的结构特点。科普类文章一般由标题(Head line),导语(Introduction),背景(Back ground),主体(Main body)和结尾(End)五部分构成。标题是文章中心思想高度而又精辟的概括,但根据历年的高考情况来看,这类阅读理解材料一般不给标题,而要同学们选择标题。导语一般位于整篇文章的首段。背景交待一个事实的起因。主体则对导语概括的事实进行详细叙述,这一部分命题往往最多,因此,阅读时,同学们要把这部分作为重点。结尾往往也是中心思想的概括,并与导语相呼应,命题者常在此要设计一道推理判断题。
3、在进行推理判断时,同学们一定要以阅读材料所提供的科学事实为依据,同时所得出的结论还应符合基本的科普常识。
科普类阅读应试策略:
【命题趋势】
阅读理解题主要考查考生对书面语篇的整体领悟能力和接受及处理具体信息的能力。试题的取材,密切联系当前我国和世界经济、科技等方面的变化,有关数据的来源真实可信。因此科普知识类文章是每年的必考题。分析历年的科普类文章我们不难发现以下特点:
1、文章逻辑性强,条理清楚,语法结构简单,用语通俗。
2、文章内容注重科技领域的新发现。内容新颖,从而使文章显得陌生,内容抽象复杂。
3、命题方面注意对具体细节的准确理解和以之为依据的推理判断。
4、以人们的日常行为或饮食健康入手,探讨利弊,诠释过程,阐述概念。
【应试对策】
许多考生在考试时感到困惑的是:为什么一些没有超越中学语法和词汇范围的篇章,读起来却不能正确理解,或者要花费很多时间才能读懂呢?这种现象的产生与阅读方法有很大的关系。例如,有的考生在考试时一见到文章就立刻开始读,结果读了半天,还不知道短文讲的是什么,试题要求了些什么,结果浪费了大量的时间,而阅读效果并不好。那么,怎样读效果才好呢?任何一种阅读方法或技巧的使用,都是由篇章特点和试题本身的要求决定的,应根据不同的体裁和试题要求采取不同的策略。
1、浏览。浏览的主要目的就是确定文章的体裁。如果文章属于人物传记、记叙文、故事、科普小品和有关社会文化、文史知识的文章,一般来说,应该先看看文章的试题考查内容,对题目类型做到心中有数,针对不同问题,在通读时有粗有细地去阅读,这样不仅能把握篇章的基本结构和逻辑线索,也能做好有关具体事实信息考查的试题。
2、挖掘寓意,掌握中心思想,推出结论。任何文章,作者在行文时都有一定的写作目的和主要话题。在通读篇章时应该吃透作者的写作意图,抓住文章的主题句,充分发挥自己的想象力和概括力,作出对中心思想的归纳和结论的推断。
3、把握篇章结构,利用上下文进行推测。高考中的阅读理解篇章往往是一个较完整的短文,其结构、思想,前后上下连贯统一。考试时应充分利用这一特点推测一些生词、短语在句中的含义,切莫盲目孤立猜测。
4、综观全篇,前后呼应。这是阅读理解的最后一步,在做完阅读理解题后,要立足于文章整体,再迅速读一遍短文,短文中的问题和答案的设置前后都是相关联的,有着一定的连续性,体现着文章的基本脉络。
登录并加入会员可无限制查看知识点解析
A. Popularity of Science Fiction |
80. |
Amongst the most popular books being written today are those which are usually classified as science fiction. Hundreds of titles are published every year and are read by all kinds of people. Furthermore, some of the most successful films of recent years have been based on science fiction stories.
81. |
It is often thought that science fiction is a fairly new development in literature, but its ancestors can be found in books written hundreds of years ago. These books were often concerned with the presentation of some form of ideal society, a theme which is still often found in modern stories.
82. |
Most of the classics of science fiction, however, have been written within the last hundred years. Books by writers such as Jules Verne and H.G. Wells, to mention just two well-known authors,
have been translated into many languages.
83. |
Modern science fiction writers don't write about men from Mars or space adventure stories. They are more interested in predicting the results of technical developments on society and the human mind; or in imagining future worlds which are a reflection of the world which we live in now.
Because of this their writing has obvious political undertones.
84. |
In an age where science fact frequently overtakes science fiction, the writers may find it difficult to keep ahead of scientific advances. Those who are sufficiently clear-sighted to see the way we are going, however, may provide a valuable lesson on how to deal with the problems which society will inevitably face as it tries to master its new technology.