Artificial Intelligence in Breast Imaging: Challenges of Integration into Clinical Practice

B. Bersu Ozcan, Bhavika K. Patel, Imon Banerjee, Basak E. Dogan

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

Abstract

Artificial intelligence (AI) in breast imaging is a rapidly developing field with promising results. Despite the large number of recent publications in this field, unanswered questions have led to limited implementation of AI into daily clinical practice for breast radiologists. This paper provides an overview of the key limitations of AI in breast imaging including, but not limited to, limited numbers of FDA-Approved algorithms and annotated data sets with histologic ground truth; concerns surrounding data privacy, security, algorithm transparency, and bias; and ethical issues. Ultimately, the successful implementation of AI into clinical care will require thoughtful action to address these challenges, transparency, and sharing of AI implementation workflows, limitations, and performance metrics within the breast imaging community and other end-users.

Original languageEnglish (US)
Pages (from-to)248-257
Number of pages10
JournalJournal of Breast Imaging
Volume5
Issue number3
DOIs
StatePublished - May 1 2023

Keywords

  • artificial intelligence
  • breast imaging
  • machine learning

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

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