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

Autor:	B Bersu Ozcan, Bhavika K Patel, Imon Banerjee, Basak E Dogan
Rok vydání:	2023
Předmět:	Radiological and Ultrasound Technology Radiology Nuclear Medicine and imaging
Zdroj:	Journal of Breast Imaging. 5:248-257
ISSN:	2631-6129 2631-6110
DOI:	10.1093/jbi/wbad007
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::011a6209345f169820335f15c738cb74 https://doi.org/10.1093/jbi/wbad007 Zobrazit plný text záznamu