Early detecting in-hospital cardiac arrest based on machine learning on imbalanced data
In-hospital cardiac arrest (IHCA) diminish the survival rate of patients, despite most of the
IHCA cases are preventable. More than 54% IHCA patient had abnormal clinical …
IHCA cases are preventable. More than 54% IHCA patient had abnormal clinical …
Validation of an artificial intelligence solution for acute triage and rule-out normal of non-contrast CT head scans
T Dyer, S Chawda, R Alkilani, TN Morgan, M Hughes… - Neuroradiology, 2022 - Springer
Purpose Non-contrast CT head scans provide rapid and accurate diagnosis of acute head
injury; however, increased utilisation of CT head scans makes it difficult to prioritise acutely …
injury; however, increased utilisation of CT head scans makes it difficult to prioritise acutely …
[HTML][HTML] Prediction of in-hospital cardiac arrest using shallow and deep learning
Sudden cardiac arrest can leave serious brain damage or lead to death, so it is very
important to predict before a cardiac arrest occurs. However, early warning score systems …
important to predict before a cardiac arrest occurs. However, early warning score systems …
Application of deep learning in neuroradiology: automated detection of basal ganglia hemorrhage using 2D-convolutional neural networks
V Desai, AE Flanders, P Lakhani - arXiv preprint arXiv:1710.03823, 2017 - arxiv.org
Background: Deep learning techniques have achieved high accuracy in image classification
tasks, and there is interest in applicability to neuroimaging critical findings. This study …
tasks, and there is interest in applicability to neuroimaging critical findings. This study …
Improving Clinician Performance in Classifying EEG Patterns on the Ictal–Interictal Injury Continuum Using Interpretable Machine Learning
AJ Barnett, Z Guo, J Jing, W Ge, PW Kaplan, WY Kong… - NEJM AI, 2024 - ai.nejm.org
Background In intensive care units (ICUs), critically ill patients are monitored with
electroencephalography (EEG) to prevent serious brain injury. EEG monitoring is …
electroencephalography (EEG) to prevent serious brain injury. EEG monitoring is …
Automatic detection of eeg epileptiform abnormalities in traumatic brain injury using deep learning
Traumatic brain injury (TBI) is a sudden injury that causes damage to the brain. TBI can have
wide-ranging physical, psychological, and cognitive effects. TBI outcomes include acute …
wide-ranging physical, psychological, and cognitive effects. TBI outcomes include acute …
Deep learning classification of cardiomegaly using combined imaging and non-imaging ICU data
D Grant, BW Papież, G Parsons, L Tarassenko… - … and Analysis: 25th …, 2021 - Springer
In this paper, we investigate the classification of cardiomegaly using multimodal data,
combining imaging data from chest radiography with routinely collected Intensive Care Unit …
combining imaging data from chest radiography with routinely collected Intensive Care Unit …
[HTML][HTML] Deep learning-assisted identification and quantification of aneurysmal subarachnoid hemorrhage in non-contrast CT scans: Development and external …
P Hu, H Zhou, T Yan, H Miu, F Xiao, X Zhu, L Shu… - NeuroImage, 2023 - Elsevier
Accurate stroke assessment and consequent favorable clinical outcomes rely on the early
identification and quantification of aneurysmal subarachnoid hemorrhage (aSAH) in non …
identification and quantification of aneurysmal subarachnoid hemorrhage (aSAH) in non …
[HTML][HTML] Neuron-specific enolase and neuroimaging for prognostication after cardiac arrest treated with targeted temperature management
Background Prognostication after cardiac arrest (CA) needs a multimodal approach, but the
optimal method is not known. We tested the hypothesis that the combination of neuron …
optimal method is not known. We tested the hypothesis that the combination of neuron …
[HTML][HTML] Weakly supervised video-based cardiac detection for hypertensive cardiomyopathy
J Chen, X Zhang, J Yuan, R Shao, C Gan, Q Ji… - BMC Medical …, 2023 - Springer
Introduction Parameters, such as left ventricular ejection fraction, peak strain dispersion,
global longitudinal strain, etc. are influential and clinically interpretable for detection of …
global longitudinal strain, etc. are influential and clinically interpretable for detection of …