Computer-aided diagnosis in the era of deep learning.

Abstract:

:Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then be used to assist clinicians in their decision-making process. The recent success of the deep learning technology in machine learning spurs new research and development efforts to improve CAD performance and to develop CAD for many other complex clinical tasks. In this paper, we discuss the potential and challenges in developing CAD tools using deep learning technology or artificial intelligence (AI) in general, the pitfalls and lessons learned from CAD in screening mammography and considerations needed for future implementation of CAD or AI in clinical use. It is hoped that the past experiences and the deep learning technology will lead to successful advancement and lasting growth in this new era of CAD, thereby enabling CAD to deliver intelligent aids to improve health care.

journal_name

Med Phys

journal_title

Medical physics

authors

Chan HP,Hadjiiski LM,Samala RK

doi

10.1002/mp.13764

subject

Has Abstract

pub_date

2020-06-01 00:00:00

pages

e218-e227

issue

5

eissn

0094-2405

issn

2473-4209

journal_volume

47

pub_type

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