Artificial Intelligence in Radiology: The Growth of Ecosystem Opportunities and Challenges

  • Aitham Suhas, Shaik Abbas, Kilari Sujan, Ketham Reddy Sai Kumar Reddy

Abstract

The rapid advancement of artificial intelligence, including medical treatment, has led to its widespread usage in many industries. AI can be a technology that transforms people dramatically and that affects the care of patients. Radiologists can help prioritize work lists by recognizing suspect and positive early review instances via AI surveillance tools. In AI programs "radiomic" information can be extracted from photos not visually recognisable, potentially boosting the diagnostic and prognostic value generated from the image data set. Predictions were made suggesting that AI will exclude radiologists. This problem has been exaggerated and radiologists are much more likely to use AI approaches into their practice. Current limits on the availability of technical competence and even processing capacity are rectified with time, and remote access solutions can also be handled. AI success is assessed by the value created: improved diagnostic certainty, faster rotation, improved patient outcomes, and improved job quality for radiologists. AI offers a potential new set of visual data analysis technologies. These novel approaches are being explored by radiologists and are likely to be prominent players in AI medical applications.

Published
2021-09-06
How to Cite
Aitham Suhas, Shaik Abbas, Kilari Sujan, Ketham Reddy Sai Kumar Reddy. (2021). Artificial Intelligence in Radiology: The Growth of Ecosystem Opportunities and Challenges. Design Engineering, 11088 - 11095. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/4103
Section
Articles