The European guideline on management of major bleeding and coagulopathy following trauma
R Rossaint, A Afshari, B Bouillon, V Cerny… - Critical Care, 2023 - Springer
Background Severe trauma represents a major global public health burden and the
management of post-traumatic bleeding continues to challenge healthcare systems around …
management of post-traumatic bleeding continues to challenge healthcare systems around …
Artificial intelligence and machine learning for hemorrhagic trauma care
Artificial intelligence (AI), a branch of machine learning (ML) has been increasingly
employed in the research of trauma in various aspects. Hemorrhage is the most common …
employed in the research of trauma in various aspects. Hemorrhage is the most common …
Pathophysiology of trauma-induced coagulopathy
There is no standard definition for trauma-induced coagulopathy (TIC). However, it could be
defined as an abnormal hemostatic response secondary to trauma. The terms “early TIC” …
defined as an abnormal hemostatic response secondary to trauma. The terms “early TIC” …
[HTML][HTML] Medical idioms for clinical Bayesian network development
Abstract Bayesian Networks (BNs) are graphical probabilistic models that have proven
popular in medical applications. While numerous medical BNs have been published, most …
popular in medical applications. While numerous medical BNs have been published, most …
Current knowledge and availability of machine learning across the spectrum of trauma science
Machine Learning holds promise for actionable decision support in trauma science, but
rigorous proof-of-concept studies are urgently needed. Future research should assess …
rigorous proof-of-concept studies are urgently needed. Future research should assess …
Identification of major hemorrhage in trauma patients in the prehospital setting: diagnostic accuracy and impact on outcome
JM Wohlgemut, E Pisirir, RS Stoner… - Trauma Surgery & …, 2024 - tsaco.bmj.com
Background Hemorrhage is the most common cause of potentially preventable death after
injury. Early identification of patients with major hemorrhage (MH) is important as treatments …
injury. Early identification of patients with major hemorrhage (MH) is important as treatments …
Machine learning in the prediction of trauma outcomes: a systematic review
Study objective Machine learning models carry unique potential as decision-making aids
and prediction tools for improving patient care. Traumatically injured patients provide a …
and prediction tools for improving patient care. Traumatically injured patients provide a …
[HTML][HTML] Updating and recalibrating causal probabilistic models on a new target population
Objective Very often the performance of a Bayesian Network (BN) is affected when applied
to a new target population. This is mainly because of differences in population …
to a new target population. This is mainly because of differences in population …
A machine learning approach for the prediction of traumatic brain injury induced coagulopathy
F Yang, C Peng, L Peng, J Wang, Y Li, W Li - Frontiers in medicine, 2021 - frontiersin.org
Background: Traumatic brain injury-induced coagulopathy (TBI-IC), is a disease with poor
prognosis and increased mortality rate. Objectives: Our study aimed to identify predictors as …
prognosis and increased mortality rate. Objectives: Our study aimed to identify predictors as …
Bias in artificial intelligence in vascular surgery
Z Tran, J Byun, HY Lee, H Boggs, EY Tomihama… - Seminars in Vascular …, 2023 - Elsevier
Application of artificial intelligence (AI) has revolutionized the utilization of big data,
especially in patient care. The potential of deep learning models to learn without a priori …
especially in patient care. The potential of deep learning models to learn without a priori …