Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study

Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study

Summary: Background: Deep learning has the potential to transform health care; however, substantial expertise is required to train such models. We sought to evaluate the utility of automated deep learning software to develop medical image diagnostic classifiers by health-care professionals with no...

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Bibliographic Details
Main Authors: Livia Faes, MD, Siegfried K Wagner, BMBCh, Dun Jack Fu, PhD, Xiaoxuan Liu, MBChB, Edward Korot, MD, Joseph R Ledsam, MBChB, Trevor Back, PhD, Reena Chopra, BSc, Nikolas Pontikos, PhD, Christoph Kern, MD, Gabriella Moraes, MD, Martin K Schmid, ProfMD, Dawn Sim, PhD, Konstantinos Balaskas, MD, Lucas M Bachmann, ProfPhD, Alastair K Denniston, ProfPhD, Pearse A Keane, MD
Format: Article
Language:English
Published: Elsevier 2019-09-01
Series:The Lancet: Digital Health
Online Access:http://www.sciencedirect.com/science/article/pii/S2589750019301086

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http://www.sciencedirect.com/science/article/pii/S2589750019301086

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