Artificial intelligence for brain diseases: A systematic review

A Segato, A Marzullo, F Calimeri, E De Momi - APL bioengineering, 2020 - pubs.aip.org
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …

Big data, machine learning, and artificial intelligence: a field guide for neurosurgeons

B Raju, F Jumah, O Ashraf, V Narayan, G Gupta… - Journal of …, 2020 - thejns.org
Big data has transformed into a trend phrase in healthcare and neurosurgery, becoming a
pervasive and inescapable phrase in everyday life. The upsurge in big data applications is a …

Nerve optic segmentation in CT images using a deep learning model and a texture descriptor

R Ranjbarzadeh, S Dorosti… - Complex & Intelligent …, 2022 - Springer
The increased intracranial pressure (ICP) can be described as an increase in pressure
around the brain and can lead to serious health problems. The assessment of ultrasound …

Dynamic prediction of mortality after traumatic brain injury using a machine learning algorithm

R Raj, JM Wennervirta, J Tjerkaski, TM Luoto… - NPJ digital …, 2022 - nature.com
Intensive care for patients with traumatic brain injury (TBI) aims to optimize intracranial
pressure (ICP) and cerebral perfusion pressure (CPP). The transformation of ICP and CPP …

Random forest–based prediction of outcome and mortality in patients with traumatic brain injury undergoing primary decompressive craniectomy

M Hanko, M Grendár, P Snopko, R Opšenák… - World neurosurgery, 2021 - Elsevier
Background Various prognostic models are used to predict mortality and functional outcome
in patients after traumatic brain injury with a trend to incorporate machine learning protocols …

A recurrent machine learning model predicts intracranial hypertension in neurointensive care patients

N Schweingruber, MMD Mader, A Wiehe, F Röder… - Brain, 2022 - academic.oup.com
The evolution of intracranial pressure (ICP) of critically ill patients admitted to a
neurointensive care unit (ICU) is difficult to predict. Besides the underlying disease and …

Current state of high-fidelity multimodal monitoring in traumatic brain injury

C Lindblad, R Raj, FA Zeiler, EP Thelin - Acta neurochirurgica, 2022 - Springer
Introduction Multimodality monitoring of patients with severe traumatic brain injury (TBI) is
primarily performed in neuro-critical care units to prevent secondary harmful brain insults …

Mining the contribution of intensive care clinical course to outcome after traumatic brain injury

S Bhattacharyay, PF Caruso, C Åkerlund, L Wilson… - npj Digital …, 2023 - nature.com
Existing methods to characterise the evolving condition of traumatic brain injury (TBI)
patients in the intensive care unit (ICU) do not capture the context necessary for …

Artificial neural networks improve early outcome prediction and risk classification in out-of-hospital cardiac arrest patients admitted to intensive care

J Johnsson, O Björnsson, P Andersson, A Jakobsson… - Critical care, 2020 - Springer
Background Pre-hospital circumstances, cardiac arrest characteristics, comorbidities and
clinical status on admission are strongly associated with outcome after out-of-hospital …

[HTML][HTML] Machine learning algorithms for predicting outcomes of traumatic brain injury: A systematic review and meta-analysis

E Courville, SF Kazim, J Vellek… - Surgical neurology …, 2023 - ncbi.nlm.nih.gov
Background: Traumatic brain injury (TBI) is a leading cause of death and disability
worldwide. The use of machine learning (ML) has emerged as a key advancement in TBI …