AIMC Topic: Cerebral Infarction
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Predicting cerebral infarction and transient ischemic attack in healthy individuals and those with dysmetabolism: a machine learning approach combined with routine blood tests.
Scientific reports
Apr 16, 2025
Ischemic cerebral infarction is the most prevalent type of stroke, causing significant disability and death worldwide. Transient ischemic attack (TIA) is a strong predictor of subsequent stroke. Individuals with dysmetabolism, such as hypertension, h...
Deep learning-based automatic segmentation of cerebral infarcts on diffusion MRI.
Scientific reports
Apr 16, 2025
We explored effects of (1) training with various sample sizes of multi-site vs. single-site training data, (2) cross-site domain adaptation, and (3) data sources and features on the performance of algorithms segmenting cerebral infarcts on Magnetic R...
Comparative Assessment of Manual Segmentation of Cerebral Infarction Lesions in Experimental Animals Based on Magnetic Resonance Imaging Using Artificial Intelligence.
Bulletin of experimental biology and medicine
Mar 28, 2025
The aim of this study was to evaluate the quality of manual segmentation of cerebral infarction lesions in experimental animals with modeled brain infarct based on magnetic resonance imaging compared to an automated artificial intelligence approach. ...
Development of machine learning-based models for predicting risk factors in acute cerebral infarction patients: a clinical retrospective study.
BMC neurology
Aug 31, 2024
OBJECTIVES: The aim of this study was to develop machine learning-based models for predicting acute cerebral infarction (ACI) in patients.
Application of interpretable machine learning algorithms to predict acute kidney injury in patients with cerebral infarction in ICU.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Apr 23, 2024
BACKGROUND: Acute kidney injury (AKI) is not only a complication but also a serious threat to patients with cerebral infarction (CI). This study aimed to explore the application of interpretable machine learning algorithms in predicting AKI in patien...
Cerebral Infarction
Decision Support Techniques
Prognosis
Humans
Machine Learning
China
Female
Aged, 80 and over
Predictive Value of Tests
Reproducibility of Results
Male
Retrospective Studies
Risk Assessment
Middle Aged
Acute Kidney Injury
Risk Factors
Diagnosis, Computer-Assisted
Intensive Care Units
Aged
Development and validation of machine learning models to predict postoperative infarction in moyamoya disease.
Journal of neurosurgery
Apr 5, 2024
OBJECTIVE: Cerebral infarction is a common complication in patients undergoing revascularization surgery for moyamoya disease (MMD). Although previous statistical evaluations have identified several risk factors for postoperative brain ischemia, the ...
An Explainable Artificial Intelligence Model to Predict Malignant Cerebral Edema after Acute Anterior Circulating Large-Hemisphere Infarction.
European neurology
Apr 2, 2024
INTRODUCTION: Malignant cerebral edema (MCE) is a serious complication and the main cause of poor prognosis in patients with large-hemisphere infarction (LHI). Therefore, the rapid and accurate identification of potential patients with MCE is essenti...
Development of a machine learning-based risk prediction model for cerebral infarction and comparison with nomogram model.
Journal of affective disorders
Jul 23, 2022
BACKGROUND: Development of a cerebral infarction (CI) risk prediction model by mining routine test big data with machine learning algorithms.
Prediction Model between Serum Vitamin D and Neurological Deficit in Cerebral Infarction Patients Based on Machine Learning.
Computational and mathematical methods in medicine
Jun 28, 2022
OBJECTIVE: Vitamin D is associated with neurological deficits in patients with cerebral infarction. This study uses machine learning to evaluate the prediction model's efficacy of the correlation between vitamin D and neurological deficit in patients...
A Deep Learning-Based Automatic Collateral Assessment in Patients with Acute Ischemic Stroke.
Translational stroke research
May 21, 2022
This study aimed to develop a supervised deep learning (DL) model for grading collateral status from dynamic susceptibility contrast magnetic resonance perfusion (DSC-MRP) images from patients with large vessel occlusion (LVO) acute ischemic stroke (...
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