AIMC Topic: Stroke

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Exploring the prognostic impact of triglyceride-glucose index in critically ill patients with first-ever stroke: insights from traditional methods and machine learning-based mortality prediction.

Cardiovascular diabetology Dec 18, 2024
BACKGROUND: The incidence and mortality of first-ever strokes have risen sharply, especially in the intensive care unit (ICU). Emerging surrogate for insulin resistance, triglyceride-glucose index (TyG), has been linked to stroke prognosis. We aims t...
Reproducibility of Results Risk Factors Aged Humans Male Machine Learning Middle Aged Databases, Factual Hospital Mortality Retrospective Studies Biomarkers Predictive Value of Tests Critical Illness Prognosis Cause of Death Risk Assessment Intensive Care Units Stroke China Female Triglycerides Length of Stay Blood Glucose Time Factors
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Prediction of stroke-associated hospital-acquired pneumonia: Machine learning approach.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Dec 12, 2024
BACKGROUND: Stroke-associated Hospital Acquired Pneumonia (HAP) significantly impacts patient outcomes. This study explores the utility of machine learning models in predicting HAP in stroke patients, leveraging national registry data and SHapley Add...
Prognosis Female Risk Factors Aged Aged, 80 and over Male Middle Aged Risk Assessment Predictive Value of Tests Humans Machine Learning Decision Support Techniques Healthcare-Associated Pneumonia Ischemic Stroke Registries Stroke Hemorrhagic Stroke
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Machine learning and deep learning algorithms in stroke medicine: a systematic review of hemorrhagic transformation prediction models.

Journal of neurology Dec 12, 2024
BACKGROUND: Acute ischemic stroke (AIS) is a major cause of morbidity and mortality, with hemorrhagic transformation (HT) further worsening outcomes. Traditional scoring systems have limited predictive accuracy for HT in AIS. Recent research has expl...
Stroke Humans Machine Learning Deep Learning Ischemic Stroke
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Residual risk prediction in anticoagulated patients with atrial fibrillation using machine learning: A report from the GLORIA-AF registry phase II/III.

European journal of clinical investigation Dec 11, 2024
BACKGROUND: Although oral anticoagulation decreases the risk of thromboembolism in patients with atrial fibrillation (AF), a residual risk of thrombotic events still exists. This study aimed to construct machine learning (ML) models to predict the re...
Thrombosis Administration, Oral Atrial Fibrillation Ischemic Attack, Transient Thromboembolism Area Under Curve Anticoagulants Registries Stroke Myocardial Infarction Risk Assessment ROC Curve Humans Logistic Models Machine Learning Ischemic Stroke Algorithms Female Risk Factors Aged Aged, 80 and over Male Middle Aged
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Subtyping strokes using blood-based protein biomarkers: A high-throughput proteomics and machine learning approach.

European journal of clinical investigation Dec 10, 2024
BACKGROUND: Rapid diagnosis of stroke and its subtypes is critical in early stages. We aimed to discover and validate blood-based protein biomarkers to differentiate ischemic stroke (IS) from intracerebral haemorrhage (ICH) using high-throughput prot...
Proteomics Cerebral Hemorrhage Diagnosis, Differential Ischemic Stroke Matrix Metalloproteinase 9 Aged Male Middle Aged Logistic Models Stroke Glial Fibrillary Acidic Protein Humans Machine Learning Biomarkers Female
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Integrating AI-driven wearable devices and biometric data into stroke risk assessment: A review of opportunities and challenges.

Clinical neurology and neurosurgery Dec 10, 2024
Stroke is a leading cause of morbidity and mortality worldwide, and early detection of risk factors is critical for prevention and improved outcomes. Traditional stroke risk assessments, relying on sporadic clinical visits, fail to capture dynamic ch...
Stroke Biometry Humans Artificial Intelligence Risk Assessment Wearable Electronic Devices
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Advancing personalised care in atrial fibrillation and stroke: The potential impact of AI from prevention to rehabilitation.

Trends in cardiovascular medicine Dec 7, 2024
Atrial fibrillation (AF) is a complex condition caused by various underlying pathophysiological disorders and is the most common heart arrhythmia worldwide, affecting 2 % of the European population. This prevalence increases with age, imposing signif...
Decision Support Techniques Precision Medicine Risk Factors Risk Assessment Treatment Outcome Humans Artificial Intelligence Machine Learning Stroke Rehabilitation Recovery of Function Predictive Value of Tests Stroke Atrial Fibrillation
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Effectiveness of unilateral lower-limb exoskeleton robot on balance and gait recovery and neuroplasticity in patients with subacute stroke: a randomized controlled trial.

Journal of neuroengineering and rehabilitation Dec 5, 2024
BACKGROUND: Impaired balance and gait in stroke survivors are associated with decreased functional independence. This study aimed to evaluate the effectiveness of unilateral lower-limb exoskeleton robot-assisted overground gait training compared with...
Gait Exoskeleton Device Stroke Rehabilitation Male Recovery of Function Humans Gait Disorders, Neurologic Middle Aged Robotics Female Treatment Outcome Postural Balance Aged Neuronal Plasticity Single-Blind Method Adult Lower Extremity Stroke
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Effects of Robot-Assisted Gait Training on Balance and Fear of Falling in Patients With Stroke: A Randomized Controlled Clinical Trial.

American journal of physical medicine & rehabilitation Dec 3, 2024
OBJECTIVE: The aim of this study was compare the effects of combined training, which included robot-assisted gait training in addition to traditional balance training, and traditional balance training alone on balance and fear of falling in patients ...
Humans Female Aged Male Middle Aged Gait Exercise Therapy Fear Stroke Rehabilitation Accidental Falls Gait Disorders, Neurologic Treatment Outcome Robotics Postural Balance Stroke
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Machine learning-based diagnostic model for stroke in non-neurological intensive care unit patients with acute neurological manifestations.

Scientific reports Nov 28, 2024
Stroke is a neurological complication that can occur in patients admitted to the intensive care unit (ICU) for non-neurological conditions, leading to increased mortality and prolonged hospital stays. The incidence of stroke in ICU settings is notabl...
Middle Aged Intensive Care Units Humans Female Machine Learning Aged Algorithms Aged, 80 and over Retrospective Studies Male ROC Curve Bayes Theorem Stroke
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