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An Overview of Current Trends, Techniques, Prospects, and Pitfalls of Artificial Intelligence in Breast Imaging

Authors Goyal S

Received 4 December 2020

Accepted for publication 22 February 2021

Published 11 March 2021 Volume 2021:14 Pages 15—25


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Professor Tarik Massoud

Video abstract presented by Swati Goyal.

Views: 386

Swati Goyal

Department of Radiodiagnosis, Government Medical College & Hospital, Bhopal, Madhya Pradesh, India

Correspondence: Swati Goyal D/16 Upant Colony, Bhopal, Madhya Pradesh, 462016 Tel +91 9424427774
Email [email protected]

Abstract: This review article aims to discuss current trends, techniques, and promising uses of artificial intelligence (AI) in breast imaging, apart from the pitfalls that may hinder its progress. It includes only the commonly used and basic terminology imperative for physicians to know. AI is not just a computerized approach but an interface between humans and machines. Apart from reducing workload and improved diagnostic accuracy, radiologists get more time for patient care or clinical work by using various machine learning techniques that augment their productivity. Inadequate data input with suboptimal pattern recognition, data extraction challenges, legal implications, and exorbitant costs are a few pitfalls that AI algorithms still face while analyzing and giving appropriate outcomes. Various machine learning approaches are used to construct prediction models for clinical decision support and ameliorating patient management. Since AI is still in its fledgling state, with many limitations for clinical implementation, clinical support and feedback are needed to avoid algorithmic errors. Hence, both machine learning and human insight complement each other in revolutionizing breast imaging.

Keywords: machine learning, augmented intelligence, ANN, CNN, CAD, GANs

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