AIMC Topic: Stroke

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Data extraction from free-text stroke CT reports using GPT-4o and Llama-3.3-70B: the impact of annotation guidelines.

European radiology experimental
BACKGROUND: To evaluate the impact of an annotation guideline on the performance of large language models (LLMs) in extracting data from stroke computed tomography (CT) reports.

Neural mechanisms underlying the improvement of gait disturbances in stroke patients through robot-assisted gait training based on QEEG and fNIRS: a randomized controlled study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robot-assisted gait training is more effective in improving lower limb function and walking ability in stroke patients compared to conventional rehabilitation, but the neural mechanisms remain unclear. This study aims to explore the effec...

Aphasia severity prediction using a multi-modal machine learning approach.

NeuroImage
The present study examined an integrated multiple neuroimaging modality (T1 structural, Diffusion Tensor Imaging (DTI), and resting-state FMRI (rsFMRI)) to predict aphasia severity using Western Aphasia Battery-Revised Aphasia Quotient (WAB-R AQ) in ...

Identification of neurological text markers associated with risk of stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Delayed or missed stroke diagnosis is associated with poor outcomes. We utilized natural language processing of notes from non-neurological emergency department (ED) encounters to identify text phrases indicating stroke presentations that...

Automated Vessel Occlusion Software in Acute Ischemic Stroke: Pearls and Pitfalls.

Stroke
Software programs leveraging artificial intelligence to detect vessel occlusions are now widely available to aid in stroke triage. Given their proprietary use, there is a surprising lack of information regarding how the software works, who is using t...

Comparison of lesion segmentation performance in diffusion-weighted imaging and apparent diffusion coefficient images of stroke by artificial neural networks.

PloS one
Stroke is the second leading cause of death, accounting for 11% of deaths worldwide. Comparing diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) images is important for stroke diagnosis, but most studies have focused on lesion...

Current utilization and impact of AI LVO detection tools in acute stroke triage: a multicenter survey analysis.

Neurological research
BACKGROUND: Artificial intelligence (AI) tools for large vessel occlusion (LVO) detection are increasingly used in acute stroke triage to expedite diagnosis and intervention. However, variability in access and workflow integration limits their potent...

O-GEST: Overground gait events detector using b-spline-based geometric models for marker-based and markerless analysis.

Journal of biomechanics
Accurate gait events detection is imperative for reliable assessment of normal and pathological gaits. However, this detection becomes challenging in the absence of force plates. Hence, this research introduces two geometric models integrated into an...

StrokeNeXt: an automated stroke classification model using computed tomography and magnetic resonance images.

BMC medical imaging
BACKGROUND AND OBJECTIVE: Stroke ranks among the leading causes of disability and death worldwide. Timely detection can reduce its impact. Machine learning delivers powerful tools for image‑based diagnosis. This study introduces StrokeNeXt, a lightwe...