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Stroke

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Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept Study.

Cerebrovascular diseases extra
INTRODUCTION: Timely thrombolytic therapy improves outcomes in acute ischemic stroke. Manual chart review to screen for thrombolysis contraindications may be time-consuming and prone to errors. We developed and tested a large language model (LLM)-bas...

Novel Robotic Balloon-Based Device for Wrist-Extension Therapy of Hemiparesis Stroke Patients.

Sensors (Basel, Switzerland)
Upper-limb paresis is one of the main complications after stroke. It is commonly associated with impaired wrist-extension function. Upper-limb paresis can place a tremendous burden on stroke survivors and their families. A novel soft-actuator device,...

Network-based predictive models for artificial intelligence: an interpretable application of machine learning techniques in the assessment of depression in stroke patients.

BMC geriatrics
BACKGROUND: Depression is a common complication after a stroke that may lead to increased disability and decreased quality of life. The objective of this study was to develop and validate an interpretable predictive model to assess the risk of depres...

Effects of Robot-Assisted Therapy for Upper Limb Rehabilitation After Stroke: An Umbrella Review of Systematic Reviews.

Stroke
BACKGROUND: Robotic rehabilitation, which provides a high-intensity, high-frequency therapy to improve neuroplasticity, is gaining traction. However, its effectiveness for upper extremity stroke rehabilitation remains uncertain. This study comprehens...

Machine Learning-Based Explainable Automated Nonlinear Computation Scoring System for Health Score and an Application for Prediction of Perioperative Stroke: Retrospective Study.

Journal of medical Internet research
BACKGROUND: Machine learning (ML) has the potential to enhance performance by capturing nonlinear interactions. However, ML-based models have some limitations in terms of interpretability.

Robust resolution improvement of 3D UTE-MR angiogram of normal vasculatures using super-resolution convolutional neural network.

Scientific reports
Contrast-enhanced UTE-MRA provides detailed angiographic information but at the cost of prolonged scanning periods, which may impose moving artifacts and affect the promptness of diagnosis and treatment of time-sensitive diseases like stroke. This st...

How Can Robotic Devices Help Clinicians Determine the Treatment Dose for Post-Stroke Arm Paresis?

Sensors (Basel, Switzerland)
Upper limb training dose after stroke is usually quantified by time and repetitions. This study analyzed upper limb motor training dose in stroke participants (N = 36) using a more comprehensive approach. Participants, classified by initial motor sev...

Risk of bias assessment of post-stroke mortality machine learning predictive models: Systematic review.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Stroke is a major cause of mortality and permanent disability worldwide. Precise prediction of post-stroke mortality is essential for guiding treatment decisions and rehabilitation planning. The ability of Machine learning models to proce...

Artificial intelligence in stroke rehabilitation: From acute care to long-term recovery.

Neuroscience
Stroke is a leading cause of disability worldwide, driving the need for advanced rehabilitation strategies. The integration of Artificial Intelligence (AI) into stroke rehabilitation presents significant advancements across the continuum of care, fro...

Rapid Blood Clot Removal via Remote Delamination and Magnetization of Clot Debris.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Micro/nano-scale robotic devices are emerging as a cutting-edge approach for precision intravascular therapies, offering the potential for highly targeted drug delivery. While employing micro/nanorobotics for stroke treatment is a promising strategy ...