As artificial intelligence(AI) systems become more advanced, we can expect them to be used more often in the world of human medicine and healthcare. AI is designed to imitate(模仿） 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.
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 quantities is a crucial factor for their success.
One of the most important areas for influencing global health is in the field of epidemiology(流行病学Predicting disease outbreaks can save millions of lives by having resources ready should the worst happen. Startup AIME 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(诊断学）. 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(心脏科医生）Rima Arnaout developed an AI that beat human experts at correctly interpreting echocardiograms(超声心动图）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 to see the patient," she said. "So we're both reading images and practicing medicine. I don't think that the second piece will be taken over so quickly. "
The acceptance of AI in medicine will continue to gather pace in the future as it becomes more widespread.
