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PratikShah_2017G-_人工智能:让诊断疾病变得更容易_

Computer algorithms today are performing incredible tasks with high accuracies , at a massive scale , using human-like intelligence. 今天的计算机算法, 正在使用类似人类的智能, 大规模的执行具有高精度的, 不可思议的任务。
performing:adj.表演的;演奏的;v.做;执行;演出;运转(perform的现在分词) incredible:adj.难以置信的,惊人的; accuracies:用法,发音,音标,搭配,同义词,反义词和例句等在线英语服务。; massive:adj.大量的;巨大的,厚重的;魁伟的; scale:n.规模;比例;鳞;刻度;天平;数值范围;v.衡量;攀登;剥落;生水垢;
And this intelligence of computers is often referred to as AI or artificial intelligence . 而这种计算机智能,通常被称为AI, 或“人工智能”。
referred:v.提到;引用;认为;指示;涉及;(refer的过去式和过去分词) artificial intelligence:n.人工智能;
AI is poised to make an incredible impact on our lives in the future. 人工智能有望在未来对我们的生活 产生令人难以置信的影响。
poised:adj.摆好姿势准备行动的; v.保持(某种姿势); impact:n.影响;效果;碰撞;冲击力;v.挤入,压紧;撞击;对…产生影响;
Today, however, we still face massive challenges in detecting and diagnosing several life-threatening illnesses, such as infectious diseases and cancer . 然而今天,在检测和诊断 几种危及生命的疾病, 比如传染病和癌症时, 我们仍然面临着大量的挑战。
detecting:n.检测;检定;v.发现;探知(detect的现在分词);adj.探测的; diagnosing:n.诊断;v.诊断(diagnose的现在分词); life-threatening:adj.威胁生命的; infectious:adj.传染的;传染性的;易传染的; diseases:n.[医]病(disease的复数);[医]疾病;[植保]病害;疾病种类; cancer:n.癌症;恶性肿瘤;
Thousands of patients every year lose their lives due to liver and oral cancer. 每年,数以千计的病人 因患上肝癌和口腔癌失去生命。
patients:n.接受治疗者,病人;(patient的复数) liver:n.肝;(动物供食用的)肝; oral:adj.口头的; n.(尤指外语考试中的)口试; (大学里的)口试;
Our best way to help these patients is to perform early detection and diagnoses of these diseases. 帮助病人最好的方式 就是对这些疾病进行 早期检测和诊断。
detection:n.侦查,探测;发觉,发现;察觉; diagnoses:n.诊断;调查分析;评价(diagnosis的复数形式);
So how do we detect these diseases today, and can artificial intelligence help? 那么,今天我们如何检测这些疾病? AI可以提供帮助吗?
In patients who, unfortunately , are suspected of these diseases, an expert physician first orders very expensive medical imaging technologies such as fluorescent imaging, CTs, MRIs, to be performed . 对于不幸被怀疑 患有这些疾病的患者, 专家医师会先要求他们照射 非常昂贵的医疗图像, 例如荧光成像,CT,MRI等。
unfortunately:adv.不幸地; suspected:v.怀疑;不信任;(suspect的过去分词和过去式) physician:n.[医]医师;内科医师; imaging:n.[物]成像;造像;v.反映;想像;作…的像;象征;(image的现在分词形式) technologies:n.技术;科技(technology的复数); fluorescent:adj.荧光的;萤光的;发亮的;n.荧光;日光灯; performed:v.表演;执行;履行;演出;工作,运转(好/不好)(perform的过去分词和过去式)
Once those images are collected, another expert physician then diagnoses those images and talks to the patient. 收集到这些图像之后, 另一位专家医师会进行诊断, 并与患者交流。
images:n.印象;声誉;形象;画像;雕像;(image的第三人称单数和复数)
As you can see , this is a very resource-intensive process , requiring both expert physicians , expensive medical imaging technologies, and is not considered practical for the developing world. 显而易见,这是个 非常耗费资源的过程, 需要两位专家医师 和昂贵的医学图像技术。 这在发展中国家被认为并不实用,
As you can see:正如你所看到的;你是知道的; resource-intensive:[环境]资源密集; process:v.处理;加工;列队行进;n.过程,进行;方法,adj.经过特殊加工(或处理)的; physicians:n.[内科]内科医生(physician的复数); practical:adj.实际的;真实的;客观存在的;n.实习课;实践课;
And in fact, in many industrialized nations, as well. 事实上,在许多 工业化国家也是如此。
industrialized:adj.工业化的;v.使工业化;将…组成产业(industrialize的过去分词);
So, can we solve this problem using artificial intelligence? 那么,我们能够用 人工智能解决这个问题吗?
Today, if I were to use traditional artificial intelligence architectures to solve this problem, 今天,如果使用传统的 人工智能架构 来解决这个问题,
traditional:传统的,惯例的, architectures:n.建筑;架构(architecture的复数);
I would require 10,000 -- 我可能需要1万张——
I repeat, on an order of 10,000 of these very expensive medical images first to be generated . 我重复一次,我首先需要 生成1万张这种非常昂贵的 医学图像。
generated:v.产生;引起;(generate的过去式和过去分词)
After that, I would then go to an expert physician, who would then analyze those images for me. 之后,我会去找一位专业医师 为我分析这些图像。
analyze:v.对…进行分析,分解(等于analyse);
And using those two pieces of information, 利用这两条信息,
I can train a standard deep neural network or a deep learning network to provide patient's diagnosis . 我可以训练标准的深度神经网络, 或深度学习网络 对患者进行诊断。
standard:n.标准;水准;旗;度量衡标准;adj.标准的;合规格的;公认为优秀的; neural network:n.神经网络; diagnosis:n.诊断;
Similar to the first approach, traditional artificial intelligence approaches suffer from the same problem. 与第一步相似, 传统人工智能方法 遭遇了同样的问题:
approaches:v.靠近,接近; n.方式,方法,态度;
Large amounts of data, expert physicians and expert medical imaging technologies. 那就是需要大量的数据、 专家医师和专业的医疗图像技术。
So, can we invent more scalable , effective and more valuable artificial intelligence architectures to solve these very important problems facing us today? 我们是否能够创造出一种 规模更大、更有效率、 同时更有价值的人工智能架构, 来解决我们今天面临的 这些重要的问题呢?
scalable:adj.可攀登的;可去鳞的;可称量的; effective:adj.有效的,起作用的;实际的,实在的;给人深刻印象; valuable:adj.有价值的;贵重的;可估价的;n.贵重物品;
And this is exactly what my group at MIT Media Lab does. 而这就是我们的团队 在MIT媒体实验室所研究的内容。
Media:n.媒体;媒质(medium的复数);血管中层;浊塞音;中脉;
We have invented a variety of unorthodox AI architectures to solve some of the most important challenges facing us today in medical imaging and clinical trials. 我们开发了各种新型AI架构, 来解决一些我们当今 在医疗图像和临床试验中 面临的最重要的挑战。
variety:n.多样;种类;杂耍;变化,多样化; unorthodox:adj.非正统的;异端的;异教的; clinical:adj.临床的;诊所的;
In the example I shared with you today, we had two goals. 在我今天分享的例子中, 包括了我们的两个目标。
Our first goal was to reduce the number of images required to train artificial intelligence algorithms. 第一个目标,是减少 用来训练人工智能算法 所需要的图片数量。
Our second goal -- we were more ambitious , we wanted to reduce the use of expensive medical imaging technologies to screen patients. 第二个目标——更大的志向, 我们希望让患者减少使用昂贵的 医疗图像技术。
ambitious:adj.野心勃勃的;有雄心的;热望的;炫耀的;
So how did we do it? 那么我们是怎样做的?
For our first goal, instead of starting with tens and thousands of these very expensive medical images, like traditional AI, we started with a single medical image. 我们的第一个目标, 相比于传统AI 从成千上万张昂贵的医疗图像开始, 我们选择从单张图像开始。
From this image, my team and I figured out a very clever way to extract billions of information packets. 根据这张图片, 我和我的团队想出了 一种非常聪明的方法 来提取数十亿个信息包。
extract:v.提取;取出;摘录;榨取;n.汁;摘录;榨出物;选粹;
These information packets included colors, pixels , geometry and rendering of the disease on the medical image. 这些信息包包含颜色、像素、形态 和疾病呈现在医疗图像上的效果。
pixels:n.像素(组成屏幕图像的最小独立元素);(pixel的复数) geometry:n.几何学;几何结构; rendering:n.演奏;扮演;表演;翻译作品;v.使成为;给予;提供;回报;(render的现在分词)
In a sense , we converted one image into billions of training data points, massively reducing the amount of data needed for training. 这样一来,我们就将一张图像 转换成了数十亿个训练数据点, 需要训练的数据量就大大减少了。
In a sense:在某种意义上; converted:adj.修改的;改变信仰的;v.转变;改变信仰(convert的过去式和过去分词形式); massively:adv.大量地;沉重地;庄严地;
For our second goal, to reduce the use of expensive medical imaging technologies to screen patients, we started with a standard, white light photograph, acquired either from a DSLR camera or a mobile phone , for the patient. 第二个目标, 是减少对患者使用医疗图像技术。 最开始,我们会从 数码单反相机或手机中 获取一张标准的白色光线照片。
white light:n.白光; acquired:adj.习得的; v.获得; (acquire的过去分词和过去式) mobile phone:移动电话
Then remember those billions of information packets? 然后,还记得那 数十亿个信息包吗?
We overlaid those from the medical image onto this image, creating something that we call a composite image. 将这些医疗图像的信息包 覆盖在这张图片上, 这时我们就创建了一张合成图像。
overlaid:v.覆盖(overlay的过去分词); composite:n.复合材料;合成物;菊科;adj.复合的;合成的;菊科的;vt.使合成;使混合;
Much to our surprise, we only required 50 -- 令人惊讶的是,我们只需要50张——
I repeat, only 50 -- of these composite images to train our algorithms to high efficiencies . 强调一下,仅仅50张—— 这些复合图像, 就能训练我们的算法提高效率。
efficiencies:n.效率(efficiency的复数);
To summarize our approach, instead of using 10,000 very expensive medical images, we can now train the AI algorithms in an unorthodox way, using only 50 of these high-resolution , but standard photographs, acquired from DSLR cameras and mobile phones, and provide diagnosis. 总结一下我们的方法, 区别于用1万张昂贵的 医疗图像训练AI算法, 我们使用了一种全新的方式, 只需要将数码相机或手机拍摄的 50张高分辨率的标准照片, 即可提供诊断。
summarize:v.总结;概述;概括;归纳; high-resolution:n.高分辨率;
More importantly, our algorithms can accept, in the future and even right now, some very simple, white light photographs from the patient, instead of expensive medical imaging technologies. 更重要的是, 在未来,甚至现在, 我们的算法可以接受 一些病人自己拍摄的白光照片, 来替代昂贵的医疗图像技术。
I believe that we are poised to enter an era where artificial intelligence is going to make an incredible impact on our future. 我相信,我们已经准备好 进入这样一个时代, 人工智能 正在对我们的未来产生 不可思议的影响。
And I think that thinking about traditional AI, which is data-rich but application-poor, we should also continue thinking about unorthodox artificial intelligence architectures, which can accept small amounts of data 我也认为相比拥有丰富数据 但应用困难的传统AI, 我们应该不断思考 非传统的人工智能架构。 它们能够接受少量数据,
and solve some of the most important problems facing us today, especially in health care . 并解决一些今天 我们所面临的重要问题, 特别是在医疗健康方面。
especially:adv.尤其;特别;格外;十分; health care:n.卫生保健;
Thank you very much. 非常感谢。
(Applause) (掌声)