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.
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...
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...
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...
Accurate segmentation of chronic stroke lesions from mono-spectral magnetic resonance imaging scans (e.g., T1-weighted images) is a difficult task due to the arbitrary shape, complex texture, variable size and intensities, and varied locations of the...
BACKGROUND: This study aimed to investigate the effects of virtual reality (VR)-based robot therapy combined with task-oriented therapy on cerebral cortex activation and upper limb function in patients with stroke.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Although there are some studies on the automatic evaluation of impairment levels after stroke using machine learning (ML) models, few have delved into the predictive capabilities of raw motion data. In this study, we captured kinematic trajectories o...
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