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Total 258 results found since Jan 2013.
A Special Report on Changing Trends in Preventive Stroke/Cardiovascular Risk Assessment Via B-Mode Ultrasonography
AbstractPurpose of ReviewCardiovascular disease (CVD) and stroke risk assessment have been largely based on the success of traditional statistically derived risk calculators such as Pooled Cohort Risk Score or Framingham Risk Score. However, over the last decade, automated computational paradigms such as machine learning (ML) and deep learning (DL) techniques have penetrated into a variety of medical domains including CVD/stroke risk assessment. This review is mainly focused on the changing trends in CVD/stroke risk assessment and its stratification from statistical-based models to ML-based paradigms using non-invasive car...
Source: Current Atherosclerosis Reports - April 30, 2019 Category: Cardiology Source Type: research
Predictive and diagnosis models of stroke from hemodynamic signal monitoring
AbstractThis work presents a novel and promising approach to the clinical management of acute stroke. Using machine learning techniques, our research has succeeded in developing accurate diagnosis and prediction real-time models from hemodynamic data. These models are able to diagnose stroke subtype with 30 min of monitoring, to predict the exitus during the first 3 h of monitoring, and to predict the stroke recurrence in just 15 min of monitoring. Patients with difficult access to a CT scan and all patients that arrive at the stroke unit of a specialized hospital will benefit from these positive results. The results obtai...
Source: Medical and Biological Engineering and Computing - May 14, 2021 Category: Biomedical Engineering Source Type: research
Accelerating Prediction of Malignant Cerebral Edema After Ischemic Stroke with Automated Image Analysis and Explainable Neural Networks
ConclusionsAn LSTM neural network incorporating volumetric data extracted from routine CT scans identified all cases of malignant cerebral edema by 24 h after stroke, with significantly fewer false positives than a fully connected neural network, regression model, and the validated EDEMA score. This preliminary work requires prospective validation but provides proof of principle that a deep learning framework could assist in selecting patients f or surgery prior to deterioration.
Source: Neurocritical Care - August 20, 2021 Category: Neurology Source Type: research
Evaluation Algorithm for the Effectiveness of Stroke Rehabilitation Treatment Using Cross-Modal Deep Learning
Comput Math Methods Med. 2022 Apr 27;2022:5435207. doi: 10.1155/2022/5435207. eCollection 2022.ABSTRACTIt is important to study the evaluation algorithm for the stroke rehabilitation treatment effect to make accurate evaluation and optimize the stroke disease treatment plan according to the evaluation results. To address the problems of poor restoration effect of positron emission tomography (PET) image and recognition restoration effect of evaluation data and so on. In the paper, we propose a stroke rehabilitation treatment effect evaluation algorithm based on cross-modal deep learning. Magnetic resonance images (MRI) and...
Source: Computational and Mathematical Methods in Medicine - May 9, 2022 Category: Statistics Authors: Lei Wang Rongxing Zhang Qinming Yu Source Type: research
Domain-general subregions of the medial prefrontal cortex contribute to recovery of language after stroke
AbstractWe hypothesized that the recovery of speech production after left hemisphere stroke not only depends on the integrity of language-specialized brain systems, but also on ‘domain-general’ brain systems that have much broader functional roles. The presupplementary motor area/dorsal anterior cingulate forms part of the cingular-opercular network, which has a broad role in cognition and learning. Consequently, we have previously suggested that variability in the rec overy of speech production after aphasic stroke may relate in part to differences in patients’ abilities to engage this domain-general brain region. T...
Source: Brain - June 27, 2017 Category: Neurology Source Type: research
Japan approves iSchemaView ’ s Rapid stroke imaging device
iSchemaView today announced that it received registration approval in Japan for its Rapid imaging platform.
The company received registration approval through the Japanese Pharmaceutical Affairs Law and through a third party review by the Japanese Assn. for the Advancement of Medical Equipment for the Rapid imaging platform.
Rapid is designed to give physicians a fast, fully automated and easy-to-interpret imaging system that can help doctors make clinical decisions about stroke.
“Stroke remains the fourth most common cause of death in Japan, and as the population ages, stroke is likely to become an increasing health...
Source: Mass Device - July 8, 2019 Category: Medical Devices Authors: Danielle Kirsh Tags: Cardiovascular Hospital Care Imaging ischemaview Source Type: news
Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research
