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Stroke

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Automatic quantitative stroke severity assessment based on Chinese clinical named entity recognition with domain-adaptive pre-trained large language model.

Artificial intelligence in medicine
BACKGROUND: Stroke is a prevalent disease with a significant global impact. Effective assessment of stroke severity is vital for an accurate diagnosis, appropriate treatment, and optimal clinical outcomes. The National Institutes of Health Stroke Sca...

Trends in stroke-related journals: Examination of publication patterns using topic modeling.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: This study aims to demonstrate the capacity of natural language processing and topic modeling to manage and interpret the vast quantities of scholarly publications in the landscape of stroke research. These tools can expedite the literatu...

Simultaneous high-definition transcranial direct current stimulation and robot-assisted gait training in stroke patients.

Scientific reports
This study investigates whether simultaneous high-definition transcranial direct current stimulation (HD-tDCS) enhances the effects of robot-assisted gait training in stroke patients. Twenty-four participants were randomly allocated to either the rob...

Machine learning decision support model for discharge planning in stroke patients.

Journal of clinical nursing
BACKGROUND/AIM: Efficient discharge for stroke patients is crucial but challenging. The study aimed to develop early predictive models to explore which patient characteristics and variables significantly influence the discharge planning of patients, ...

Assessing the clinical reasoning of ChatGPT for mechanical thrombectomy in patients with stroke.

Journal of neurointerventional surgery
BACKGROUND: Artificial intelligence (AI) has become a promising tool in medicine. ChatGPT, a large language model AI Chatbot, shows promise in supporting clinical practice. We assess the potential of ChatGPT as a clinical reasoning tool for mechanica...

Combining Transcranial Direct Current Stimulation With Hand Robotic Rehabilitation in Chronic Stroke Patients: A Double-Blind Randomized Clinical Trial.

American journal of physical medicine & rehabilitation
OBJECTIVE: This study aimed to assess the impact of combining transcranial direct current stimulation with end-effector robot-assisted treatment on upper limb function, spasticity, and hand dexterity in chronic stroke patients.

Detection and Assessment of Point-to-Point Movements During Functional Activities Using Deep Learning and Kinematic Analyses of the Stroke-Affected Wrist.

IEEE journal of biomedical and health informatics
Stoke is a leading cause of long-term disability, including upper-limb hemiparesis. Frequent, unobtrusive assessment of naturalistic motor performance could enable clinicians to better assess rehabilitation effectiveness and monitor patients' recover...

Towards a diagnostic tool for neurological gait disorders in childhood combining 3D gait kinematics and deep learning.

Computers in biology and medicine
Gait abnormalities are frequent in children and can be caused by different pathologies, such as cerebral palsy, neuromuscular disease, toe walker syndrome, etc. Analysis of the "gait pattern" (i.e., the way the person walks) using 3D analysis provide...

Point-Of-Care low-field MRI in acute Stroke (POCS): protocol for a multicentric prospective open-label study evaluating diagnostic accuracy.

BMJ open
INTRODUCTION: Fast and accurate diagnosis of acute stroke is crucial to timely initiate reperfusion therapies. Conventional high-field (HF) MRI yields the highest accuracy in discriminating early ischaemia from haemorrhages and mimics. Rapid access t...