In 1976, Maxmen1 predicted that artificial intelligence (AI) in the 21st century would usher in "the post-physician era," with health care provided by paramedics and computers. Today, the mass extinction of physicians remains unlikely. However, as outlined by Hinton2 in a related Viewpoint, the emergence of a radically different approach to AI, called deep learning, has the potential to effect major changes in clinical medicine and health care delivery.
Reinforcement learning has traditionally occupied a niche status in the world of artificial intelligence. But reinforcement learning has started to assume a larger role in many AI initiatives in the past few years. Its application sweet spot is in calculation of optimal actions to be taken by agents in environmentally contextualized decision scenarios. Using trial-and-error approaches to maximize an algorithmic reward function, reinforcement learning is well suited to many adaptive-control and multiagent automation applications in IT operations management, energy, health care, commerce, finance, transportation, and finance. And it's being used to train the AI that powers both its traditional focus areas--robotics, gaming, and simulation--and a new generation of AI solutions in edge analytics, natural language processing, machine translation, computer vision, and digital assistants.
The endoscope and colonoscope were first developed in 1880s to look inside the body. Specialists use their expertise and experience to examine the medical images. But sometimes, human error and backend issues can result in misdiagnosis. Population increase and more cases of internal diseases are overloading the medical industry in many major cities in the world. In turn, the demand of medical specialists continues to soar.
Another 177 companies (level 2) are developing projects using deep learning with dedicated resources in staff. And more than 350 companies (level 1) are experimenting with deep learning in their labs. Given how early deep learning is as a technology, the majority of companies investing in deep learning are IT and software businesses. However, we discovered interesting champions in other industries that are adopting deep learning as well. Given that deep learning has early roots in image processing, it is exciting to see health care companies like Siemens Healthcare and GE Healthcare leading the pack, along with research institutions like the NIH and Lawrence Livermore National Labs.