The Rise of Digital Doctors数字医生的兴起

罗宾·费伦

As AI technology becomes more sophisticated， we can expect them to be used more often in the world of human medicine and healthcare. But is it possible to create medical AIs that rapidly outperform doctors in certain tasks？ Find out all the ways AI is helping the healthcare world.

AI is designed to mimic the human brain in decision making and learning， so with the computing power to learn tasks in days or even hours， it is possible to create medical AIs that rapidly outperform doctors in certain tasks.

Most of the AI systems working in medicine employ smart algorithms， with the machine and deep learning techniques， and are supplemented by speech recognition and computer or machine vision to make their decisions.

It will be some time before researchers can develop artificial general intelligence systems capable of abstracting knowledge and developing their own experiences to share with other AIs. But firms like Microsoft， Google， Apple， IBM and Facebook are gearing themselves up1 to deliver the most advanced AI personalized healthcare possible for patients around the world.

Data plays a hugely important role in helping AI systems learn about human medicine. AI systems are trained on large data sets gathered from real-life cases. Providing detailed patient information in volume is a crucial factor for their success.

One of the most important areas for influencing global health is in the field of epidemiology. Predicting disease outbreaks can save millions of lives by having resources ready should the worst happen. Startup AIME2 has successfully combined public health data with machine learning and AI to create a prediction engine capable of anticipating epidemics months in advance with great accuracy.

Another field where medical AIs are making rapid advances is in diagnostics. Doctors base a lot of decisions on information from X-ray， CT and MRI images. Speeding up diagnoses from patient scans can rapidly improve patient care and outcomes.

Computer vision AIs use pattern recognition to work through these images with incredible speed and accuracy. They have been able to outperform junior doctors and even senior specialists in some tests.

Cardiologist Rima Arnaout developed an AI that beat human experts at correctly interpreting echocardiograms by 92 percent to 79 percent. She said that despite the result there is no prospect of AI replacing human doctors any time soon. “As cardiologists， we read the images and then go see the patient，” she said. “So were both reading images and practicing medicine. I dont think that the second piece will be taken over so quickly.”

The results are obviously impressive， but being aware of the hype around AI in medicine is just as important for both physicians and patients. The Institute of Electrical and Electronics Engineers （IEEE） has a handy visualization tool to show where smart algorithms and humans were better at detecting health problems.

People are sharing more and more of their health data through apps on mobile and wearable devices. Now virtual and voice assistants using natural language processing and AI are being prepped to provide healthcare on-demand. Amazons Alexa3 has partnered with the UKs National Health Service （NHS） to provide users with health advice， but it could also be used to tell if you are having a heart attack.

Governments in many countries face the prospect of ageing populations. This will likely see the expansion of AI services， including robotic helpers. Robots designed specifically to interact with people could help solve the problems of isolation and loneliness that affect many older people.

Georgia Institute of Technology built an experimental robot called PR2 that taught itself how to put a gown onto humans in just one day. Those skills could be readily adapted for people in hospitals and care homes around the world.

We already have mobile robotic telepresence （MRT） systems available to provide support to the ill and elderly. This class of social robots are effectively remote-controlled video screens on wheels that allow medics， carers， or relatives to interact with people in their own homes.

Pet androids like Aibo the robot dog， or Paro （a baby seal） provide companionship and learn from their interactions about each owners preferences.

More humanoid robots include the ‘emotional robot BUDDY， which is able to provide social interaction， be a personal assistant， play multimedia and games， and look after the elderly， according to its makers. Mabu is another wide-eyed humanoid robot that uses AI and a recipe of best practices from human doctors to help monitor heart failure patients.

Robot AIs can also be put to work in hospitals to help doctors and nurses spend more time with their patients. Moxi is a robot assistant that helps staff by completing general tasks such as delivering lab samples， collecting laundry or gathering medical supplies.

Even in the surgical suite， there is support from AI robotic surgery systems that reduce variations4 between surgeons which affect patient recovery. Dr. John Birkmeyer， a chief clinical officer of Sound Physicians5 said， “we know that a surgeons skill， particularly with new or difficult procedures， varies widely， with huge implications for patient outcomes and cost. AI can both reduce that variation， and help all surgeons improve—even the best ones.”

The acceptance of AI in medicine will continue to gather pace in the future as it becomes more widespread. Its promise to enhance patient care by reducing errors in diagnosis， improving the ability to predict disease， and providing assistance to busy clinicians is also the promise of keeping humans at the centre of healthcare.

随着人工智能技术日趋成熟，其在人类医学和医疗保健领域的应用会越来越广泛。但有可能开发出在某些工作上迅速超越人类医生的医学人工智能技术吗？我们来看看人工智能在医疗保健领域都有哪些应用。

人工智能旨在模拟人脑进行决策和学习，因为计算机有超强学习能力，几天甚至几个小时就能完成某项学习任务，因此开发出在某些工作上迅速超越人类医生的医学人工智能是有可能的。

大多数医学领域的人工智能系统采用智能算法，利用机器学习和深度学习技术，辅以语音识别和计算机或机器视觉来做决策。

研制出能够提炼所学知识和积累经验与其他人工智能进行分享的通用人工智能系统尚需时日，但微软、谷歌、苹果、国际商用机器公司（IBM）和脸书等公司正在准备为全世界的患者提供最先进的人工智能个性化医疗服务。

在帮助人工智能系统掌握人类医学知识的过程中，数据扮演着极其重要的角色。人工智能系统通过来源于真实病例的大型数据集学习。提供大量而详实的病患数据是其成功的关键因素。

流行病学是影响全球健康最重要的医学领域之一。预测疾病的暴发，从而在最坏的情况发生时有所准备，可以拯救千百万人的生命。初创企业AIME成功地将公共卫生数据与机器学习和人工智能结合起来，开发出的预测工具能够提前数月对流行病进行精准预测。

医学人工智能发展迅速的另一个领域是诊断学。医生做的很多决定都基于X光、CT和核磁共振成像的检验结果，加快医学影像的诊断速度可以迅速提高病患护理质量和改善治疗效果。

计算机视觉人工智能利用模式识别技术处理影像，速度之快、准确度之高都达到惊人的程度。在一些测试中，其表现已超过了初级医生甚至资深专科医生。

心脏病学家里马·阿尔瑙特开发了一种人工智能技术，解读超声心动图的准确率为92%，比人类专家（79%）更胜一筹。但她认为，即便如此，短期内人工智能也无法取代人类医生。“作为心脏病专家，我们看过影像后还要进行面诊。”她说，“我们既解读影像又问诊和触诊。我认为这第二部分的工作不会这么快就被人工智能取代。”

科研成果令人瞩目，但意识到人工智能在医学领域被过度宣传对医生和患者同样重要。电气与电子工程师协会有便于操作的可视化工具，可演示智能算法与人类在探查疾病方面各有哪些优势。

人们越来越多地通过手机应用和可穿戴设备分享自己的健康数据。目前正在研制可运用自然语言处理和人工智能技术的虚拟语音助手，根据需要提供医疗保健服务。亚马逊公司的Alexa人工智能助手与英国国家医疗服务体系合作，为用户提供健康咨询，也可以用来判断你是否心脏病发作。

很多国家的政府即将面对人口老龄化问题，这可能促使包括机器人助手在内的人工智能服务的发展。许多老年人易产生孤独感，专门设计用来与人互动的机器人有助于克服这些问题。

佐治亚理工学院制造了一款叫做PR2的实验机器人，一天内就自学掌握了如何给人穿外罩，此技能随时可以推广到全世界的医院和看护中心。

现在已经有了移动机器人远程呈现系统，能够为病人和老年人提供帮助。此类社交机器人实际上是带轮子的远程控制视频屏幕，医生、护工或亲属可通过它们在自己家里与需要照顾的人互动。

机器狗Aibo或小海豹Paro这样的宠物机器人可以提供陪伴，并且能在互动中了解自己主人的喜好。

还有更多的类人机器人，如“有情感的”机器人Buddy，据制造者介绍，它懂得社交互动，可以做个人助理，会使用多媒体和玩游戏，还能照顾老人。Mabu是另外一款大眼类人机器人，它利用人工智能和人类医生提供的最佳治疗方案来帮助监护心脏衰竭患者。

人工智能机器人还可以在医院帮忙，让医生和护士有更多的时间照料病人。Moxi是一款机器人助手，它可以帮工作人员完成诸如运送实验室样品、取走脏衣服或收集医疗耗材等日常工作。

即使在外科手术室里也能用到人工智能自动手术系统，这类系统缩小了不同外科医生的技术差异，这些差异会影响患者康复效果。Sound Physicians的首席临床官约翰·伯克迈耶医生说：“我们知道，外科医生间的技术差异是很大的，尤其是在做新的或复杂的手术时，对医疗效果和治疗费用都有很大影响。而人工智能既可以缩小这类差异，又可以帮助所有外科医生——甚至是最好的外科醫生——提升技术。”

将来，随着人工智能越来越普及，其在医疗领域的应用也会继续加快步伐。有望通过减少误诊、提高疾病预测能力和为忙碌的临床医生提供帮助来提高病患护理水平，实际上也是在医疗保健工作中做到以人为本。

（译者为“《英语世界》杯”翻译大赛获奖选手）