Crossmark

Invasive or More Direct Measurements Can Provide an Objective Early-Stopping Ceiling for Training Deep Neural Networks on Non-invasive or Less-Direct Biomedical Data

Crossref DOI link: https://doi.org/10.1007/s42979-022-01553-8

Published Online: 2023-01-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Bartlett, Christopher W. https://orcid.org/0000-0001-7837-6348
Bossenbroek, Jamie

Ueyama, Yukie

McCallinhart, Patricia

Peters, Olivia A.

Santillan, Donna A.

Santillan, Mark K.

Trask, Aaron J.

Ray, William C.
Funding

Funding for this research was provided by:

National Institutes of Health (UL1TR002537, R00HL116769, R21EB026518, R01HD08994)

National Institutes of Health (P50HD105556)
License Information

Text and Data Mining valid from 2023-01-12

Version of Record valid from 2023-01-12
More Information

Article History

Received: 19 February 2022

Accepted: 8 December 2022

First Online: 12 January 2023

Declarations

:

: The authors declare that there is no conflict of interest.

: Animal work was approved by the Nationwide Children’s Hospital Institutional Animal Care and Use Committee (protocol number: AR18-0001). For analysis of the de-identified placenta data, the Nationwide Children’s Hospital Institutional Review Board reviewed the project and determined that it did not require further review (STUDY00000950). For the University of Iowa, a human subjects research determination was completed for this study and the IRB determined that our use of coded samples and data are not human subjects research (IRB202201716).

Document is current

Any future updates will be listed below