AIMC Topic: Stroke

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Emergency medical services providers' perspectives on the use of artificial intelligence in prehospital identification of stroke- a qualitative study in Norway and Sweden.

BMC emergency medicine
BACKGROUND: Stroke is a large and increasing health challenge, leading to acquired physical disability and mortality. A rapid diagnostic assessment in the acute phase of a stroke is crucial and highly time dependent. Studies suggest that artificial i...

Effects and neural mechanisms of a brain-computer interface-controlled soft robotic glove on upper limb function in patients with subacute stroke: a randomized controlled fNIRS study.

Journal of neuroengineering and rehabilitation
BACKGROUND AND PURPOSE: The brain-computer interface-based soft robotic glove (BCI-SRG) holds promise for upper limb rehabilitation in subacute stroke patients, yet its efficacy and neural mechanisms are unclear. This study aimed to investigate the t...

Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients.

BMC medical informatics and decision making
BACKGROUND: Coronary artery disease (CAD) remains a leading cause of global mortality, with stroke constituting a significant complication among patients undergoing coronary revascularization procedures, such as percutaneous coronary intervention (PC...

Post-stroke aphasia analysis using topological alterations in brain functional networks.

Journal of neural engineering
. Nearly one-third of stroke patients develop aphasia. Although the function of classical language areas (e.g. Broca's area, Wernicke's area) has been widely characterized, the network reorganization mechanisms behind specific language dysfunctions i...

Deep learning to identify stroke within 4.5 h using DWI and FLAIR in a prospective multicenter study.

Scientific reports
To enhance thrombolysis eligibility in acute ischemic stroke, we developed a deep learning model to estimate stroke onset within 4.5 h using diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) images. Given the variabilit...

A comprehensive explainable AI approach for enhancing transparency and interpretability in stroke prediction.

Scientific reports
Stroke is among the leading causes of death, especially among old adults. Thus, the mortality rate and severe cerebral disability can be avoided when stroke is diagnosed at its early stages, followed by subsequent treatment. There is no doubt that he...

Enhancing stroke risk prediction through class balancing and data augmentation with CBDA-ResNet50.

Scientific reports
Accurate prediction of stroke risk at an early stage is essential for timely intervention and prevention, especially given the serious health consequences and economic burden that strokes can cause. In this study, we proposed a class-balanced and dat...

Cost-effectiveness analysis of robotic exoskeleton versus conventional physiotherapy for stroke rehabilitation in Singapore from a health system perspective.

BMJ open
OBJECTIVES: This study conducted a comprehensive probabilistic cost-effectiveness analysis comparing robotic exoskeleton therapy to conventional physiotherapy for stroke rehabilitation in Singapore, focusing on three patient groups categorised by the...

Neuroimaging and biological markers of different paretic hand outcomes after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Hand dysfunction significantly affects independence after stroke, with outcomes varying across individuals. Exploring biomarkers associated with the paretic hand can improve the prognosis and guide personalized rehabilitation. However, wh...

Research on transcranial magnetic stimulation for stroke rehabilitation: a visual analysis based on CiteSpace.

European journal of medical research
OBJECTIVE: This study aimed to analyze recent research and emerging trends in transcranial magnetic stimulation (TMS) for stroke rehabilitation.