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。……