Navigating the ocean of big data in neurocritical care

R Dhar, G Meyfroidt - Neurocritical Care, 2022 - Springer
Artificial intelligence (AI) will inevitably infiltrate and increasingly influence clinical practice
and research in neurocritical care. The question is no longer whether or even when this will …

An end-end deep learning framework for lesion segmentation on multi-contrast mr images—an exploratory study in a rat model of traumatic brain injury

BP Kn, A Cs, A Mohammed, KK Chitta, XV To… - Medical & Biological …, 2023 - Springer
Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra—areas of
secondary neural injury which are crucial targets for therapeutic interventions. Segmenting …

Prediction of prednisolone dose correction using machine learning

H Sato, Y Kimura, M Ohba, Y Ara… - Journal of Healthcare …, 2023 - Springer
Wrong dose, a common prescription error, can cause serious patient harm, especially in the
case of high-risk drugs like oral corticosteroids. This study aims to build a machine learning …

Friedman's Gradient-Boosting Algorithm Predicts Lactate-Pyruvate Ratio Trends in Cases of Intracerebral Hemorrhages

J Kang, I Shah, S Shahrestani, CQ Nguyen, PM Chen… - World Neurosurgery, 2024 - Elsevier
Objective The local effects of an intracerebral hemorrhage (ICH) on surrounding brain tissue
can be detected bedside using multimodal brain monitoring techniques. The aim of this …

Detection of emotional and behavioural changes after traumatic brain injury: A comprehensive survey

N Vutakuri - Cognitive Computation and Systems, 2023 - Wiley Online Library
Traumatic brain injury (TBI) can affect normal brain function and may be caused by a vehicle
accident, falling, and so on. The purpose of this survey is to provide clear knowledge of TBI …

Prediction analysis of TBI 24-h survival outcome based on machine learning

Y Yang, L Zhou, J Luo, J Xue, J Liu, J Zhang, Z Wang… - Heliyon, 2024 - cell.com
Background Traumatic brain injury (TBI) is the major reason for the death of young people
and is well known for its high mortality and morbidity. This paper aim to predict the 24h …

Artificial intelligence in the management of neurological disorders: its prevalence and prominence

PS Mathew, AS Pillai - Augmenting Neurological Disorder Prediction and …, 2022 - Elsevier
Abstract According to the World Health Organization, millions of people worldwide are
affected by neurological disorders. Patients dealing with this condition have a lot of …

[HTML][HTML] Künstliche Intelligenz in der Neurointensivmedizin

N Schweingruber, C Gerloff - Der Nervenarzt, 2021 - ncbi.nlm.nih.gov
Die Methoden der künstlichen Intelligenz (KI) halten Einzug in die Medizin. Die KI-assistierte
Medizin ist die Zukunft, die es mitzugestalten gilt. Insbesondere supervidiertes …

Multiple Machine Learning Approaches Based on Postoperative Prediction of Pulmonary Complications in Patients With Emergency Cerebral Hemorrhage Surgery

X Jing, X Wang, H Zhuang, X Fang, H Xu - Frontiers in Surgery, 2022 - frontiersin.org
Objective This study aimed to create a prediction model of postoperative pulmonary
complications for the patients with emergency cerebral hemorrhage surgery. Methods …

Applicability of artificial intelligence in neuropsychological rehabilitation of patients with brain injury

V Medenica, L Ivanovic, N Milosevic - Applied Neuropsychology …, 2024 - Taylor & Francis
Neuropsychological rehabilitation plays a critical role in helping those recovering from brain
injuries restore cognitive and functional abilities. Artificial Intelligence, with its potential, may …