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Comment
. 2023 Sep 20;10(1):43.
doi: 10.1186/s40779-023-00476-6.

Enhancing the clinical relevance of haemorrhage prediction models in trauma

Sankalp Tandle  1   2 , Jared M Wohlgemut  3   4 , Max E R Marsden  3   5 , Erhan Pisirir  6 , Evangelia Kyrimi  6 , Rebecca S Stoner  3   4 , William Marsh  6 , Zane B Perkins  3   4 , Nigel R M Tai  3   4   5
Affiliations
Comment

Enhancing the clinical relevance of haemorrhage prediction models in trauma

Sankalp Tandle et al. Mil Med Res. .
No abstract available

Keywords: Artificial intelligence; Blood transfusion; Injury; Machine learning; Massive transfusion; Prediction; Trauma.

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Conflict of interest statement

JMW received funding from the Royal College of Surgeons of England for salary support during the conduct of the study. RSS received funding from the Royal College of Surgeons of Edinburgh for salary support during the conduct of the study. The other authors declare that they have no competing interests.

Comment on

References

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