AIMC Topic: Stroke
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Electrocardiogram-Based Artificial Intelligence to Discriminate Cardioembolic Stroke and Stratify Risk of Atrial Fibrillation After Stroke.
Circulation. Arrhythmia and electrophysiology
Aug 28, 2024
Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting.
Journal of the American Heart Association
Aug 27, 2024
BACKGROUND: Transfemoral carotid artery stenting (TFCAS) carries important perioperative risks. Outcome prediction tools may help guide clinical decision-making but remain limited. We developed machine learning algorithms that predict 1-year stroke o...
Digital health in stroke: a narrative review.
Arquivos de neuro-psiquiatria
Aug 26, 2024
Digital health is significantly transforming stroke care, particularly in remote and economically diverse regions, by harnessing mobile and wireless technologies, big data, and artificial intelligence (AI). Despite the promising advancements, a notab...
Machine learning models for outcome prediction in thrombectomy for large anterior vessel occlusion.
Annals of clinical and translational neurology
Aug 23, 2024
OBJECTIVE: Predicting long-term functional outcomes shortly after a stroke is challenging, even for experienced neurologists. Therefore, we aimed to evaluate multiple machine learning models and the importance of clinical/radiological parameters to d...
Establishment and validation of a risk stratification model for stroke risk within three years in patients with cerebral small vessel disease using a combined MRI and machine learning algorithm.
SLAS technology
Aug 21, 2024
BACKGROUND: Cerebral small vessel disease (CSVD) is a major cause of stroke, particularly in the elderly population, leading to significant morbidity and mortality. Accurate identification of high-risk patients and timing of stroke occurrence plays a...
Optimizing Acute Stroke Segmentation on MRI Using Deep Learning: Self-Configuring Neural Networks Provide High Performance Using Only DWI Sequences.
Journal of imaging informatics in medicine
Aug 13, 2024
Segmentation of infarcts is clinically important in ischemic stroke management and prognostication. It is unclear what role the combination of DWI, ADC, and FLAIR MRI sequences provide for deep learning in infarct segmentation. Recent technologies in...
Feedback control of heart rate during robotics-assisted tilt table exercise in patients after stroke: a clinical feasibility study.
Journal of neuroengineering and rehabilitation
Aug 12, 2024
BACKGROUND: Patients with neurological disorders including stroke use rehabilitation to improve cognitive abilities, to regain motor function and to reduce the risk of further complications. Robotics-assisted tilt table technology has been developed ...
Combining robotics and functional electrical stimulation for assist-as-needed support of leg movements in stroke patients: A feasibility study.
Medical engineering & physics
Aug 3, 2024
PURPOSE: Rehabilitation technology can be used to provide intensive training in the early phases after stroke. The current study aims to assess the feasibility of combining robotics and functional electrical stimulation (FES), with an assist-as-neede...
Botulinum Toxin Type A (BoNT-A) Use for Post-Stroke Spasticity: A Multicenter Study Using Natural Language Processing and Machine Learning.
Toxins
Aug 2, 2024
We conducted a multicenter and retrospective study to describe the use of botulinum toxin type A (BoNT-A) to treat post-stroke spasticity (PSS). Data were extracted from free-text in electronic health records (EHRs) in five Spanish hospitals. We incl...
The stroke outcome optimization project: Acute ischemic strokes from a comprehensive stroke center.
Scientific data
Aug 2, 2024
Stroke is a leading cause of disability, and Magnetic Resonance Imaging (MRI) is routinely acquired for acute stroke management. Publicly sharing these datasets can aid in the development of machine learning algorithms, particularly for lesion identi...
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