Bayesian deep learning outperforms clinical trial estimators of intracerebral and intraventricular hemorrhage volume-Reference-Cited by-同舟云学术

Bayesian deep learning outperforms clinical trial estimators of intracerebral and intraventricular hemorrhage volume

Published:2022-04-17 Issue:5 Volume:32 Page:968-976
ISSN:1051-2284
Container-title:Journal of Neuroimaging
language:en
Short-container-title:Journal of Neuroimaging

Author:

Sharrock Matthew F.¹^ORCID,Mould W. Andrew²,Hildreth Meghan²,Ryu E. Paul²,Walborn Nathan²,Awad Issam A.³,Hanley Daniel F.²,Muschelli John⁴

Affiliation:

1. Division of Neurocritical Care, Department of Neurology University of North Carolina at Chapel Hill Chapel Hill North Carolina USA

2. Division of Brain Injury Outcomes, Department of Neurology Johns Hopkins University Baltimore Maryland USA

3. Neurovascular Surgery Program, Section of Neurosurgery, Department of Surgery University of Chicago Medicine and Biological Sciences Chicago Illinois USA

4. Department of Biostatistics, Bloomberg School of Public Health Johns Hopkins University Baltimore Maryland USA

Publisher

Wiley

Subject

Neurology (clinical),Radiology, Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jon.12997

Reference50 articles.

1. Intraventricular hemorrhage and hydrocephalus after spontaneous intracerebral hemorrhage: results from the STICH trial

2. Volume of intracerebral hemorrhage. A powerful and easy-to-use predictor of 30-day mortality.

3. Primary intraventricular hemorrhage in adults.

4. The ICH Score

5. Intracerebral hemorrhage: External validation and extension of a model for prediction of 30-day survival

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