AIMC Topic: Stroke

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SpinalTRAQ: A Novel Pipeline for Volumetric Cervical Spinal Cord Analysis Identifies the Corticospinal Tract Synaptic Projectome in Healthy and Post-stroke Mice.

eNeuro
The corticospinal tract (CST) is essential for forelimb-specific fine motor skills. In rodents, it undergoes extensive structural remodeling across development, injury, and disease states, with major implications for motor function. A vast body of li...

Identifying determinants of readmission and death post-stroke using explainable machine learning.

PloS one
BACKGROUND: Stroke remains a global health challenge with high rates of mortality and rehospitalization placing significant demands on healthcare systems. Identifying factors that determine outcomes of post-hospitalization improves resource allocatio...

Neural xenografts contribute to long-term recovery in stroke via molecular graft-host crosstalk.

Nature communications
Stroke remains a leading cause of disability due to the brain's limited ability to regenerate damaged neural circuits. Here, we show that local transplantation of iPSC-derived neural progenitor cells (NPCs) improves brain repair and long-term functio...

Soft robotic gloves versus mirror therapy: a long-term comparative study on hand function and motor recovery in post-stroke rehabilitation.

Journal of rehabilitation medicine
OBJECTIVE: This study aimed to compare the long-term effects of soft robotic gloves (SRGs) and mirror therapy on hand function and motor recovery in post-stroke patients.

Strokeformer: A novel deep learning paradigm training transformer-based architecture for stroke prognosis prediction.

PloS one
Stroke, a common neurological disorder, is considered one of the leading causes of death and disability worldwide. Stroke prognosis issues involve using clinical characteristics collected from patients presented in tabular form to determine whether t...

Machine learning-based prediction model for post-stroke cerebral-cardiac syndrome: a risk stratification study.

Scientific reports
Cerebral-cardiac syndrome (CCS) is a severe cardiac complication following acute ischemic stroke, often associated with adverse outcomes. This study developed and validated a machine learning (ML) model to predict CCS using clinical, laboratory, and ...

A review of machine learning applications in heart health.

Biomedical engineering online
The application of machine learning in healthcare continues to gain attention as researchers attempt to prove its potential for the enhancement of diagnosis and prognosis accuracy. Although many applications of machine learning have been well studied...

Artificial intelligence with feature fusion empowered enhanced brain stroke detection and classification for disabled persons using biomedical images.

Scientific reports
Brain stroke is an illness which affects almost every age group, particularly people over 65. There are two significant kinds of strokes: ischemic and hemorrhagic strokes. Blockage of brain vessels causes an ischemic stroke, while cracks in blood ves...

Current Landscape and Future Directions Regarding Generative Large Language Models in Stroke Care: Scoping Review.

JMIR medical informatics
BACKGROUND: Stroke has a major impact on global health, causing long-term disability and straining health care resources. Generative large language models (gLLMs) have emerged as promising tools to help address these challenges, but their application...

Development and interpretation of a machine learning risk prediction model for post-stroke depression in a Chinese population.

Scientific reports
Current evidence for predictive models of post-stroke depression (PSD) risk based on machine learning (ML) remains limited. The aim of this study is to develop a superior predictive model based on ML algorithms for PSD in the Chinese population. We r...