Deep learning with electronic health records for short-term fracture risk identification : crystal bone algorithm development and validation

Almog, Y.A., Rai, A., Zhang, P. et al. (8 more authors) (2020) Deep learning with electronic health records for short-term fracture risk identification : crystal bone algorithm development and validation. Journal of Medical Internet Research, 22 (10). e22550.

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 The Authors. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.10.2020. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
Keywords: AI; EHR; NLP; artificial intelligence; bone; deep learning; electronic health record; fracture; low bone mass; machine learning; natural language processing; osteoporosis; prediction
Dates:
  • Accepted: 12 September 2020
  • Published (online): 16 October 2020
  • Published: 16 October 2020
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Sheffield Teaching Hospitals
Depositing User: Symplectic Sheffield
Date Deposited: 06 Nov 2020 14:07
Last Modified: 06 Nov 2020 14:07
Status: Published
Publisher: JMIR Publications Inc.
Refereed: Yes
Identification Number: https://doi.org/10.2196/22550
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