Methodological quality of multivariate prognostic models for intracranial haemorrhages in intensive care units: a systematic review
Saved in:
Main Authors: | Denis Frasca, Fanny Feuillet, Maxime Leger, Raphaël Cinotti, Yohann Foucher, Jeanne Simon-Pimmel, Laetitia Bodet-Contentin, Etienne Dantan |
---|---|
Format: | article |
Language: | EN |
Published: |
BMJ Publishing Group
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/24fb4f55b9bb4e6ea5e8ffd8354fbf3c |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
G-computation and machine learning for estimating the causal effects of binary exposure statuses on binary outcomes
by: Florent Le Borgne, et al.
Published: (2021) -
Detection and classification of intracranial haemorrhage on CT images using a novel deep-learning algorithm
by: Ji Young Lee, et al.
Published: (2020) -
G-computation, propensity score-based methods, and targeted maximum likelihood estimator for causal inference with different covariates sets: a comparative simulation study
by: Arthur Chatton, et al.
Published: (2020) -
Haemorrhagic Bowel Syndrome in Fattenig Pigs
by: Novotný Jaroslav, et al.
Published: (2016) -
CSF proteomics of patients with hydrocephalus and subarachnoid haemorrhage
by: Sokół Bartosz, et al.
Published: (2019)