To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressive craniectomy (DC) in patients with severe traumatic brain injury (TBI) and to demonstrate its pote...
Signal transduction and targeted therapy
Jun 23, 2025
Traumatic brain injury (TBI) is a major public health concern associated with an increased risk of neurodegenerative diseases including Alzheimer's disease (AD), Parkinson's disease (PD), and chronic traumatic encephalopathy, yet the underlying molec...
International journal of molecular sciences
May 28, 2025
Traumatic brain injury (TBI) induces complex molecular and cellular responses, often leading to vision deterioration and potential mortality. Current objective diagnostic methods are limited, necessitating the development of novel tools to assess dis...
International journal of molecular sciences
May 24, 2025
Traumatic brain injury (TBI) triggers a cascade of molecular and cellular disturbances, including apoptosis, inflammation, and destabilization of neuronal connections. The transcription factor p53 plays a pivotal role in regulating cell fate followin...
BACKGROUND: Unsupervised traumatic brain injury (TBI) lesion detection aims to identify and segment abnormal regions, such as cerebral edema and hemorrhages, using only healthy training data. Recent advancements in generative models have achieved suc...
Traumatic brain injury (TBI) is a significant global health issue with high morbidity and mortality rates. Recent studies have shown that machine learning algorithms outperform traditional logistic regression models in predicting functional outcomes ...
Ventilator-associated pneumonia significantly increases morbidity, mortality, and healthcare costs among patients with traumatic brain injury. Accurately predicting risk can facilitate earlier interventions and improve patient outcomes. This study le...
Current neurology and neuroscience reports
Feb 19, 2025
PURPOSE OF REVIEW: This review investigates the use of machine learning (ML) in prognosticating outcomes for traumatic brain injury (TBI). It underscores the benefits of ML models in processing and integrating complex, multimodal data-including clini...
Machine learning (ML) offers precise predictions and could improve patient care, potentially replacing traditional scoring systems. A retrospective study at Emtiaz Hospital analyzed 3,180 traumatic brain injury (TBI) patients. Nineteen variables were...
BACKGROUND: Older persons comprise most traumatic brain injury (TBI)-related hospitalizations and deaths and are particularly susceptible to fall-induced TBIs. The combination of increased frailty and susceptibility to clinical decline creates a sign...
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