Integration of Teleradiology and Artificial Intelligence: Opportunities and Challenges

Abstract

Over the past few decades, radiology has become an increasingly important part of diagnosis and healthcare delivery in general, and correspondingly the burden on radiologists continues to increase with greater imaging volumes and stringent reporting turnaround time expectations, resulting in radiology reporting delays and errors. To bridge the gap, teleradiology has played an important role over the past two decades, but given the mismatch between the dramatically increased utilization of radiologic imaging and the relatively constant number of trained radiologists entering practice, additional solutions are necessary. Teleradiology and Artificial Intelligence have exceptional synergies from the perspective of both being technology enabled healthcare delivery mechanisms that address the same fundamental issue of radiologist shortages. These synergies lead to a multiplier effect in terms of Teleradiology enabling Artificial Intelligence algorithms to be deployed at scale globally over a short time frame to rapidly achieve greater impact than either solution can individually. This article will review the opportunities whereby Artificial Intelligence can further enhance Teleradiology practice, as well as explore the challenges that exist at this time that may potentially delay this process of integration.

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