考研英语题源报刊《天然》中英文双语精读版-人工智能如何前进癌症检测…(考研英语题源报刊阅读提高篇)



考研英语题源报刊《天然》中英文双语精读版-人工智能如何前进癌症检测…(考研英语题源报刊阅读提高篇)缩略图

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上期翻译答案
in massachusetts, one of the top five states/ reporting first-time jobless claims last week, the biggest surge came in the health-care and social assistance sector.
马萨诸塞州上星期陈述的初度赋闲请求数排在前五位,其间赋闲人数增幅最大的首要为清洁保健和社会协助部分。
1.one of the top5 state…,作为刺进语,是对massachusetts的润饰
2.one of the top five states(that) reporting first-time jobless claims last week,这儿reporting first-time…前面省掉了 that,是对 the top5 state的润饰限制
我看到许多同学把reporting first-time jobless…翻译成了“报导了上星期初度赋闲…”,可是我们可以细心分析一下,假定咱们要写“报导了上星期初度赋闲…”,那么咱们的report大约用曩昔式才对!
《本期内容》
导读
尽管正确确诊很重要,但前期发现癌症也能前进生计率。在美国,许多妇女从四五十岁初步每年都要做乳房x光查看。这就发生了许多的成像数据。成像数据与机器学习相联系,是不是可以前进确诊功率?

双语阅览
regina barzilay, a computer scientist at the massachusetts institute of technology (mit) in cambridge, wanted to see if a machine could use those data to draw a more accurate picture of a person’s risk ofdeveloping breast cancer. barzilay collected almost 89,000mammogramsfrom nearly 40,000 women who had beenscreenedover a 4-year period, and checked the images against a nationaltumourregistry to determine which women were eventually diagnosed with breast cancer.

剑桥麻省理工学院的核算机科学家雷吉娜·巴兹莱想看看机器是不是可以使用这些数据来更精确地描绘出一自个患乳腺癌的风险。巴兹莱搜集了近4万名女人在4年内承受筛查构成的近8.9万张乳房x光片,并将这些印象与国家肿瘤挂号处进行比对,以断定哪些女人究竟
考研英语题源报刊《天然》中英文双语精读版-人工智能如何前进癌症检测…(考研英语题源报刊阅读提高篇)插图
被确诊出患有乳腺癌。
she then trained a machine-learning algorithm witha subset ofthose images and outcomes, before testing the system to see how well it predicted cancer risk. the computer put 31% of the women who eventually developed breast cancer into the highest risk group. but the standard tyrer–cuzick model that physicians use to estimate risk — based on factors such as age, family history of cancer, and age at firstmenstrualperiod and atmenopause— placed only 18% in that group, even when physicians added measurements of breast density from mammograms to the model.

接着她用这些图像和成果的数据集构成了一个机器学?惴ǎ缓蟛檠檎飧鎏逑担纯此虏獍┲⒎缦盏淖饔萌绾巍:怂慊烤够疾∨说?1%列为风险最高的一组。翻译划线句,长按文末小程序码进行打卡,答案下期发布~
the researchers are continuing to improve the model, says adam yala, a phd student at mit who works with barzilay on the project. if the mit system can learn to differentiate between people who will develop cancer within five years and those who won’t, yala says, it might allow physicians to personalize screening schedules and offer frequent mammograms only to those whose early scans show they are at high risk.

和巴兹莱一同参加项意图麻省理工学院博士生亚当亚拉说,研讨人员正在持续改进这一模型。亚拉说,假定麻省理工学院的体系可以学会区别我们是不是将在五年内罹患癌症,这可以会让医生拟定特性化的筛查方案,而且只为那些前期扫描闪现他们处于高风险的人供给频频的乳房x光查看。
researchers at 谷歌 are also trying to improve cancer screening. medical groups in the united states and canada already recommend screening certain people who are at high risk of lung cancer using computed tomography (ct) scans based on low-dose x-rays, and the same screeningprotocolis under consideration in the european union. computer scientists at 谷歌 wanted to see whether they could predict which people would go on to develop lung cancer by using ai to analyse low-dose ct scans of the lungs.

谷歌的研讨人员也在尽力改进癌症筛查。美国和加拿大的医疗团队现已主张运用根据低剂量x射线的核算机断层扫描(ct)对某些肺癌高危人群进行筛查,欧盟也在思考选用相同的筛查方案。谷歌的核算机科学家想看看他们能否经过使用人工智能分析肺部的低剂量ct扫描成果,来猜测哪些人会患上肺癌。
in people with only one scan available, the ai outperformed all of the six radiologists who also examined the ct scans toassessrisk of lung cancer. the ai reduced the number of false positives by 11% and false negative by 5%. when there were two scans, the radiologists did about as well as the computer. researchers hope that more accurate screening will lead to more effective treatment. “ultimately what we want is patients to get their cancers caught earlier,” says daniel tse, a medical doctor at 谷歌 health who led the project.

在只进行了一次扫描的人群中,人工智能的体现跨越了6名用ct扫描评价患肺癌风险的放射科医生。人工智能削减了11%的假阳性和5%的假阴性成果。当进行两次扫描时,放射科医生的体现和核算机差不多。研讨人员期望,更精确的筛查将发生更有用的医治。“归根究竟,咱们想要的是让患者更早地发现他们的癌症,”该项目担任人、谷歌安康(一款电子病历效能)的医生丹尼尔·谢说。
这篇文章节选自:nature(天然)
发布时刻:2021.03.25
作者:neil savage
原文标题:how ai is improving cancer diagnostics

词汇堆集
1.mammogram

英 [mmɡrm] 美 [mmɡrm]

n. 乳房x光查看

2.screen

英 [skrin] 美 [skrin]

n. 屏幕、影片(总称)、掩蔽物、妨碍、(医疗的)查看、纱门
vt. 查看、躲藏、放映(影片)、检查(是不是可以信赖)、选择

3.tumour

英 [tumr] 美 [tumr]

n. 肿瘤

4.menstrual

英 [menstrul] 美 [menstrul]

adj. 例假的、行为期的

5.menopause

英 [menpz] 美 [menpz]

n. (妇女的)更年期

6.protocol

英 [protkɑl] 美 [protkɑl]

n. 礼节、礼仪、协议、文本、草案
vt. 拟定

7.assess

英 [ses] 美 [ses]

vt. 判定、评价、对…纳税


词组分配
1.develop breast cancer 患乳腺癌
2.a subset of …的一个子集

写作句总结
computer scientists at 谷歌 wanted to see whether they could predict which people would go on to develop lung cancer by using ai to analyse low-dose ct scans of the lungs.
规划:… want to see whether they could predict ….
他们想要看看是不是能猜测…
例句:the soothsayers want to see whether they could predict the horoscope of each sign in the coming year.

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