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【健康报道】Google AI系统可以改善乳腺癌的检测 Google AI System Could Improve Breast Cancer Detection

来源:慢速英语   时间:2020-01-10 16:39:49

A Google artificial intelligence system was as good as expert radiologists at discovering which women had breast cancer in a new study. The system made the findings from thousands of mammogram images, researchers in the United States and Britain reported.


在一项新研究中,谷歌人工智能系统和放射线专家一样擅长发现哪些女性患有乳腺癌。美国和英国的研究人员报道说,该系统是从数千张乳房X线照片中得出的结果。


This is the newest study to show that artificial intelligence, or AI, may improve the accuracy of mammograms. Breast cancer affects one in eight women around the world. The study was published in the journal Nature.


这是最新的研究,表明人工智能或AI可以提高乳房X线照片的准确性。乳腺癌影响全世界八分之一的女性。该研究发表在《自然》杂志上。


The American Cancer Society says radiologists miss about 20 percent of breast cancers in mammograms. And many women who get the tests have a false positive result at some point. A false positive result shows a woman with cancer even though she does not have it.


美国癌症协会说,放射线医生在乳房X光照片中错过了大约20%的乳腺癌。而且,许多接受测试的女性在某个时候都会有假阳性结果。假阳性结果表明女性患有癌症,即使她没有。


The findings of the study were developed with DeepMind AI, which joined with Google Health in September.


该研究的结果由DeepMind AI开发,并于9月与Google Health一起加入。


The study results represent a big step toward the possibility of early breast cancer detection, said Mozziyar Etemadi. He is one of the study writers and based at Northwestern Medicine in Chicago.


Mozziyar Etemadi说,这项研究结果代表了朝着早期发现乳腺癌的方向迈出的一大步。他是研究作家之一,居住在芝加哥的西北医学。


The team included researchers at Imperial College London and Britain's National Health Service. Together, they trained the AI system to identify breast cancers on tens of thousands of mammograms.


该团队包括伦敦帝国理工学院和英国国家卫生局的研究人员。他们一起训练了AI系统,以识别成千上万的乳房X线照片上的乳腺癌。


They then compared the AI system's performance with the actual results from a set of 25,856 mammograms in the United Kingdom and 3,097 from the United States.


然后,他们将AI系统的性能与英国25856张乳房X线照片和美国3097张乳房X线照片的实际结果进行了比较。


The study showed the AI system could identify cancers with a similar level of accuracy to expert radiologists. At the same time, it reduced the number of false positive results by 5.7 percent in the American patients and 1.2 percent in the British patients.

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研究表明,人工智能系统可以识别出与放射线专家相似的癌症。同时,它在美国患者中减少了5.7%的假阳性结果,在英国患者中减少了1.2%的假阳性结果。


It also cut the number of false negatives, where tests are wrongly listed as normal, by 9.4 percent in the American group, and 2.7 percent in the British group.


它还将误报为正常测试的误报数减少了,美国组减少了9.4%,英国组减少了2.7%。


These results show differences in how mammograms are read. In the U.S., only one radiologist reads the results and the tests are done every one to two years. In Britain, the tests are done every three years, and each is read by two radiologists. When they disagree, a third radiologist reads it.


这些结果表明,乳腺X线照片的读取方式有所不同。在美国,只有一名放射科医生读取结果,并且每隔一到两年进行一次测试。在英国,测试每三年进行一次,每一次都由两名放射科医生读取。当他们不同意时,第三位放射科医生将其阅读。


Seeing the signs


看到迹象


In a separate test, the researchers put the AI system against six radiologists and found it performed better at correctly detecting breast cancers.


在另一项测试中,研究人员将AI系统对付了六名放射科医生,发现它在正确检测乳腺癌方面表现更好。


Connie Lehman is chief of the breast imaging department at Harvard's Massachusetts General Hospital. She said the results agree with findings from many groups using AI to improve cancer detection in mammograms, including her own work.


康妮·莱曼(Connie Lehman)是哈佛大学麻萨诸塞州综合医院乳房影像科的负责人。她说,结果与许多小组的研究结果相吻合,这些小组使用AI来改善乳房X线照片中的癌症检测,包括她自己的工作。


The idea of using computers to improve cancer detection has been around for years. And computer-aided detection or CAD systems are common in mammography health centers, but CAD has not improved performance in health practice.


使用计算机来改善癌症检测的想法已经存在多年了。而且,计算机辅助检测或CAD系统在乳腺X射线照相术健康中心很常见,但是CAD并没有改善健康实践中的性能。


The issue, Lehman said, is that current CAD programs were trained to identify things human radiologists can see. But with AI, computers learn to find cancers based on the actual results of thousands of mammograms. So AI has the possibility of going beyond human ability to identify small signs the human eye and brain cannot.


雷曼说,问题是当前的CAD程序已经过训练,可以识别放射线医生可以看到的东西。但是,借助人工智能,计算机可以根据成千上万的乳房X线照片的实际结果学习发现癌症。因此,人工智能有可能超越人类的能力来识别人眼和大脑无法识别的小标志。


Mozziyar Etemadi added that the study has shown, in tens of thousands of mammograms, that AI can "make a very well-informed decision."


Mozziyar Etemadi补充说,该研究已经在成千上万的乳房X线照片中显示出AI可以“做出非常明智的决定”。


A few limitations


一些限制


The study has some limitations. Most of the tests were done using the same type of imaging equipment, and the U.S. group had a lot of patients with confirmed breast cancers.


该研究有一些局限性。大多数测试是使用相同类型的成像设备完成的,而美国小组中有很多确诊为乳腺癌的患者。


Importantly, the team has not yet shown that the tool improves patient care, said Dr. Lisa Watanabe. She is chief medical officer of CureMetrix, a company whose AI mammogram program won U.S. approval last year.


重要的是,团队尚未显示该工具可以改善患者的护理,Lisa Watanabe博士说。她是CureMetrix的首席医疗官,该公司的AI乳房X线照片程序去年获得了美国的批准。


She noted that AI is only helpful if it creates noticeable progress for radiologists.


她指出,人工智能只有在放射医师取得显着进步的情况下才有帮助。


Etemadi agreed that those studies are needed, as is regulatory approval, a process that could take many years.


Etemadi同意,需要进行这些研究,同时需要获得监管机构的批准,这一过程可能需要很多年。


重点词汇:

Words in This Story:

radiologist – n. a doctor whose expertise is using some forms of radiation (such as X-rays) to diagnose and treat diseases

mammogram – n. a photograph of a woman's breasts made by X-rays

accuracy – n. the quality of having no errors or mistakes

detection – n. the act or process of discovering, finding, or noticing something

false positive – n. a test result which incorrectly indicates that a particular condition is present

false negative – n. a test result which incorrectly indicates that a particular condition is absent


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