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Total 258 results found since Jan 2013.

Neurofunctional correlates of a neurorehabilitation system based on eye movements in chronic stroke impairment levels: A pilot study
ConclusionThese promising results have a potential application as a new game-based neurorehabilitation approach to enhance the motor activity of stroke patients.
Source: Brain and Behavior - July 12, 2023 Category: Neurology Authors: B árbara R. García‐Ramos, Rebeca Villarroel, José L. González‐Mora, Consuelo Revert, Cristián Modroño Tags: ORIGINAL ARTICLE Source Type: research

Superhero Joey: Five-year-old fights moyamoya disease
It’s been said that not all heroes wear capes — but Joey Gallagher owns several. The five-year-old has already amassed a collection of superhero gear, from a Superman Halloween costume to a t-shirt emblazoned with the Batman logo. Yet even the most diehard comic book fan would likely admit that feats like flying, leaping tall buildings and fighting bad guys don’t hold a candle to the challenges this little boy has already surmounted. Just last June, Joey was out of town with his family when he had what his parents, Leila and Scott, feared was a seizure. Clinicians in the emergency department dismissed the event as he...
Source: Thrive, Children's Hospital Boston - April 4, 2017 Category: Pediatrics Authors: Jessica Cerretani Tags: Diseases & Conditions Our Patients’ Stories childhood stroke Dr. Edward Smith Dr. Michael Scott moyamoya Moyamoya Disease Program Source Type: news

Automated ASPECTS on Noncontrast CT Scans in Patients with Acute Ischemic Stroke Using Machine Learning FUNCTIONAL
CONCLUSIONS: The proposed automated ASPECTS scoring approach shows reasonable ability to determine ASPECTS on NCCT images in patients presenting with acute ischemic stroke.
Source: American Journal of Neuroradiology - January 11, 2019 Category: Radiology Authors: Kuang, H., Najm, M., Chakraborty, D., Maraj, N., Sohn, S. I., Goyal, M., Hill, M. D., Demchuk, A. M., Menon, B. K., Qiu, W. Tags: FUNCTIONAL Source Type: research

Generalizing post-stroke prognoses from research data to clinical data
Publication date: Available online 14 October 2019Source: NeuroImage: ClinicalAuthor(s): Robert Loughnan, Diego L. Lorca-Puls, Andrea Gajardo-Vidal, Valeria Espejo-Videla, Céline R. Gillebert, Dante Mantini, Cathy J. Price, Thomas M.H. HopeAbstractAround a third of stroke survivors suffer from acquired language disorders (aphasia), but current medicine cannot predict whether or when they might recover. Prognostic research in this area increasingly draws on datasets associating structural brain imaging data with outcome scores for ever-larger samples of stroke patients. The aim is to learn brain-behavior trends from these ...
Source: NeuroImage: Clinical - October 15, 2019 Category: Radiology Source Type: research

Quantifying the Impact of Chronic Ischemic Injury on Clinical Outcomes in Acute Stroke With Machine Learning
Acute stroke is often superimposed on chronic damage from previous cerebrovascular events. This background will inevitably modulate the impact of acute injury on clinical outcomes to an extent that will depend on the precise anatomical pattern of damage. Previous attempts to quantify such modulation have employed only reductive models that ignore anatomical detail. The combination of automated image processing, large-scale data, and machine learning now enables us to quantify the impact of this with high-dimensional multivariate models sensitive to individual variations in the detailed anatomical pattern. We introduce and ...
Source: Frontiers in Neurology - January 23, 2020 Category: Neurology Source Type: research

Enhanced white matter reorganization and activated brain glucose metabolism by enriched environment following ischemic stroke: Micro PET/CT and MRI study.
This study aimed to examine the effects of post-ischemic EE treatment on the brain remodeling using magnetic resonance imaging (MRI) and 18F-FDG positron emission tomography (PET). Male Sprague-Dawley rats were subjected to permanent middle cerebral artery occlusion (MCAO) and housed in standard environment (SE) or EE for consecutive 30 days. Cognitive testing was performed using the Morris water maze. White matter structural modifications were detected by MRI combined with histological analysis. In addition, PET scanning with 18F-FDG as a molecular probe was conducted to detect brain energy metabolism. Our results showed ...
Source: Neuropharmacology - June 28, 2020 Category: Drugs & Pharmacology Authors: Li M, Zhao Y, Zhan Y, Yang L, Feng X, Lu Y, Lei J, Zhao T, Wang L, Zhao H Tags: Neuropharmacology Source Type: research

Deep Learning-Enabled Clinically Applicable CT Planbox for Stroke With High Accuracy and Repeatability
ConclusionsCAPITAL-CT generated standard and reproducible images that could simplify the work of radiologists, which would be of great help in the follow-up of stroke patients and in multifield research in neuroscience.
Source: Frontiers in Neurology - March 11, 2022 Category: Neurology Source Type: research

Unsupervised Deep Learning for Stroke Lesion Segmentation on Follow-up CT Based on Generative Adversarial Networks FUNCTIONAL
CONCLUSIONS: An unsupervised generative adversarial network can be used to obtain automated infarct lesion segmentations with a moderate Dice similarity coefficient and good volumetric correspondence.
Source: American Journal of Neuroradiology - August 8, 2022 Category: Radiology Authors: van Voorst, H., Konduri, P. R., van Poppel, L. M., van der Steen, W., van der Sluijs, P. M., Slot, E. M. H., Emmer, B. J., van Zwam, W. H., Roos, Y. B. W. E. M., Majoie, C. B. L. M., Zaharchuk, G., Caan, M. W. A., Marquering, H. A., on behalf of the CONTR Tags: FUNCTIONAL Source Type: research

Machine learning prediction of symptomatic intracerebral hemorrhage after stroke thrombolysis: a cross-cultural validation in Caucasian and Han Chinese cohort
CONCLUSION: The established SVM model is feasible for predicting the risk of sICH after thrombolysis quickly and efficiently in both Caucasian and Han Chinese cohort.PMID:36225969 | PMC:PMC9549180 | DOI:10.1177/17562864221129380
Source: Adv Data - October 13, 2022 Category: Epidemiology Authors: Junfeng Liu Xinyue Chen Xiaonan Guo Renjie Xu Yanan Wang Ming Liu Source Type: research

Deep learning prediction of stroke thrombus red blood cell content from multiparametric MRI
CONCLUSIONS: The CNN was able to accurately predict thrombus RBC content using multiparametric MR images, and could provide a means to guide treatment strategy in acute ischemic stroke.PMID:36437762 | DOI:10.1177/15910199221140962
Source: Interventional Neuroradiology - November 28, 2022 Category: Radiology Authors: Spencer D Christiansen Junmin Liu Maria Bres Bullrich Manas Sharma Melfort Boulton Sachin K Pandey Luciano A Sposato Maria Drangova Source Type: research

Ctbrain machine learning predicts stroke thrombolysis result
Conclusions This proof-of-concept study shows that machine learning methods applied to acute stroke CT-scans potentially offers automation, and improved performance in SICH prediction following thrombolysis. Larger-scale cohorts, and incorporation of CT perfusion/angiography data, should be tested with such methods.
Source: Journal of Neurology, Neurosurgery and Psychiatry - September 9, 2014 Category: Neurosurgery Authors: Epton, S., Bentley, P., Ganesalingam, J., Dias, A., Mahady, K., Rinne, P., Sharma, P., Halse, O., Mehta, A., Rueckert, D. Tags: Abstracts Source Type: research

DWI Negative Stroke: Learning Points For Imaging In Acute Stroke (P1.037)
CONCLUSIONS: Clinical exam bears more weight than imaging in suspected brainstem infarcts. With the increasing use of DWI as the imaging of choice in acute stroke, DWI negative stroke must be considered in patients who present with classic brain stem infarcts with negative imaging to prevent delay in therapy as these patients may still be a candidate for thrombolysis.Disclosure: Dr. Nalleballe has nothing to disclose. Dr. JADEJA has nothing to disclose. Dr. Bollu has nothing to disclose. Dr. Onteddu has nothing to disclose.
Source: Neurology - April 8, 2015 Category: Neurology Authors: Nalleballe, K., Jadeja, N., Bollu, P., Onteddu, S. Tags: Cerebrovascular Disease and Interventional Neurology: Case Reports Source Type: research

AI Becoming Prevalent in Identifying Stroke, Head Trauma
Another company is throwing its hat into the ring to use artificial intelligence to help identify bleeds, fractures and other critical abnormalities in head CT scans. San Mateo, CA-based Qure.ai released the results of a clinical validation study confirming its algorithm’s near-radiologist performance on 21, 000 patients and has made a dataset of almost 500 AI-analyzed head CT scans available for download. The results have been published in a research paper on Cornell University's online distribution system for research, arXiv.org. The paper is titled “Development and Validation of Deep Learning Algorithms for Detectio...
Source: MDDI - May 3, 2018 Category: Medical Devices Authors: Omar Ford Tags: Business Digital Health Source Type: news