AIMC Topic: Stroke
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Deep learning-based classification of speech disorder in stroke and hearing impairment.
PloS one
Jan 1, 2025
BACKGROUND AND OBJECTIVE: Speech disorders can arise from various causes, including congenital conditions, neurological damage, diseases, and other disorders. Traditionally, medical professionals have used changes in voice to diagnose the underlying ...
The use of artificial intelligence to identify ophthalmic biomarkers in cardiovascular disease and stroke: a narrative review.
Sao Paulo medical journal = Revista paulista de medicina
Jan 1, 2025
BACKGROUND: Cardiovascular disease (CVD) and stroke are among the leading causes of death worldwide.
Optimizing Stroke Detection Using Evidential Networks and Uncertainty-Based Refinement.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 1, 2025
Evaluating neurological impairments post-stroke is essential for assessing treatment efficacy and managing subsequent disabilities. Conventional clinical assessment methods depend largely on clinicians' visual and physical evaluations, resulting in c...
Artificial Intelligence in Transcranial Doppler Ultrasonography.
Current medical imaging
Jan 1, 2025
Transcranial Doppler is an instrumental ultrasound method capable of providing data on various brain pathologies, in particular, the study of cerebral hemodynamics in stroke, quickly, economically, and with repeatability of the data themselves. Howev...
Predictive Value of Machine Learning Models for Cerebral Edema Risk in Stroke Patients: A Meta-Analysis.
Brain and behavior
Jan 1, 2025
INTRODUCTION: Stroke patients are at high risk of developing cerebral edema, which can have severe consequences. However, there are currently few effective tools for early identification or prediction of this risk. As machine learning (ML) is increas...
Fair prediction of 2-year stroke risk in patients with atrial fibrillation.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2024
OBJECTIVE: This study aims to develop machine learning models that provide both accurate and equitable predictions of 2-year stroke risk for patients with atrial fibrillation across diverse racial groups.
[Construction and external validation of a non-invasive pre-hospital screening model for stroke patients: a study based on artificial intelligence DeepFM algorithm].
Zhonghua wei zhong bing ji jiu yi xue
Nov 1, 2024
OBJECTIVE: To construct a non-invasive pre-hospital screening model and early based on artificial intelligence algorithms to provide the severity of stroke in patients, provide screening, guidance and early warning for stroke patients and their famil...
Letter to Editor Regarding "Use of Artificial Intelligence Software to Detect Intracranial Aneurysms: A Comprehensive Stroke Center Experience".
World neurosurgery
Nov 1, 2024
Artificial intelligence (AI) is increasingly significant in neurosurgery, enhancing differential diagnosis, preoperative evaluation, and surgical precision. A recent study in World Neurosurgery evaluated AI's role in aneurysm detection, comparing con...
Effect of Upper Robot-Assisted Training on Upper Limb Motor, Daily Life Activities, and Muscular Tone in Patients With Stroke: A Systematic Review and Meta-Analysis.
Brain and behavior
Nov 1, 2024
BACKGROUND: Upper limb rehabilitation robot is a relatively new technology, but its effectiveness remains debatable due to the inconsistent results of clinical trials. This article intends to assess how upper limb rehabilitation robots help the funct...
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