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Thrall, J.H., Li, X., Li, Q., Cruz, C., Do, S., Dreyer, K. and Brink, J. (2018) Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success. Journal of the American College of Radiology, 15, 504-508.
https://doi.org/10.1016/j.jacr.2017.12.026

has been cited by the following article:

• TITLE: The Role of Digital Technology and Artificial Intelligence in Diagnosing Medical Images: A Systematic Review

  AUTHORS: Rani Ahmad

  KEYWORDS: Artificial Intelligence, Machine Learning, Radiology

  JOURNAL NAME: Open Journal of Radiology, Vol.11 No.1, March 5, 2021

  ABSTRACT: The provision of up-to-date medical information on digital technology and AI systems in journals, clinical practices, and textbooks informing radiologists about patient care has resulted in faster, more reliable, and cheaper image interpretation. This study reviews 27 articles regarding the application of digital technology and artificial intelligence (AI) in radiological scholarship, looking at the incorporation of electronic health system records, digital radiology imaging databases, IT environments, and machine learning—the latter of which has emerged as the most popular AI approach in modern medicine. This article examines the emerging picture surrounding archiving and communication systems in the implementation phase of AI technologies. It explores the most appropriate clinical requirements for the use of AI systems in practice. Continued development in the integration of automated systems, probing the use of information systems, databases, and records, should result in further progress in radiological theory and practice.