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Deep learning and medical imaging - 2018

Research Area:  Machine Learning

Abstract:

AI medical imaging research, such as in the studies described above, is rapidly increasing, and commercial applications are beginning to emerge, it is important to understand that although radiology is a somewhat large financial market, the driving force for AI development is much larger. Huge financial markets such as internet giants like Google, Facebook, Baidu and Alibaba, self-driving cars, robotics and many others, are the driving force for the financial and ingenuity investment in the development of both the software and the hardware aspects of AI. New developments in machine learning, and more specifically deep learning, will likely have major implications on human society in the near future, and this advancement has already been termed by some, the fourth industrial revolution (23). In a summary of the Intersociety Summer Conference of the American College of Radiology (ACR) it has been stated that Data science will change radiology practice as we know it more than anything since Roentgen, and it will happen more quickly than we expect.. pretending this will not disrupt radiology is naive.Some radiology experts emphasize the importance of remaining optimistic about future opportunities of data science, as well as about the active role of radiologists in the AI revolution, a role that entails engagement rather than replacement. The future is unknown, the AI revolution has just recently started, and as humans we struggle in estimating exponential processes. It is important for medical institutions to invest in the understanding of this new technology, in order to be best prepared for the upcoming changes.

Author(s) Name:  Eyal Klang

Journal name:  J Thorac Disv

Conferrence name:  

Publisher name:  AME Publishing

DOI:  10.21037/jtd.2018.02.76

Volume Information:  Volume 10,Issue (3),2018 Mar