AIMC Topic: Ischemic Stroke

Clear Filters Showing 81 to 90 of 229 articles

Machine learning-based predictive model for the development of thrombolysis resistance in patients with acute ischemic stroke.

BMC neurology Aug 26, 2024
BACKGROUND: The objective of this study was to establish a predictive model utilizing machine learning techniques to anticipate the likelihood of thrombolysis resistance (TR) in acute ischaemic stroke (AIS) patients undergoing recombinant tissue plas...
Humans Machine Learning Male Fibrinolytic Agents Middle Aged Retrospective Studies Ischemic Stroke Tissue Plasminogen Activator Female Thrombolytic Therapy Drug Resistance Aged Aged, 80 and over
View on PubMed DOI

Center of Pressure- and Machine Learning-based Gait Score and Clinical Risk Factors for Predicting Functional Outcome in Acute Ischemic Stroke.

Archives of physical medicine and rehabilitation Aug 24, 2024
OBJECTIVES: To investigate whether machine learning (ML)-based center of pressure (COP) analysis for gait assessment, when used in conjunction with clinical information, offers additive benefits in predicting functional outcomes in patients with acut...
Ischemic Stroke Stroke Rehabilitation Gait Gait Disorders, Neurologic Humans Pressure Aged, 80 and over Female Gait Analysis Risk Factors Aged Male Machine Learning Middle Aged Prospective Studies Recovery of Function
View on PubMed DOI

Machine learning models for outcome prediction in thrombectomy for large anterior vessel occlusion.

Annals of clinical and translational neurology Aug 23, 2024
OBJECTIVE: Predicting long-term functional outcomes shortly after a stroke is challenging, even for experienced neurologists. Therefore, we aimed to evaluate multiple machine learning models and the importance of clinical/radiological parameters to d...
Stroke Outcome Assessment, Health Care Endovascular Procedures Thrombectomy Male Middle Aged Ischemic Stroke Registries Humans Machine Learning Prognosis Female Aged Aged, 80 and over
View on PubMed DOI

A Deep Learning Approach to Predict Recanalization First-Pass Effect following Mechanical Thrombectomy in Patients with Acute Ischemic Stroke.

AJNR. American journal of neuroradiology Aug 9, 2024
BACKGROUND AND PURPOSE: Following endovascular thrombectomy in patients with large-vessel occlusion stroke, successful recanalization from 1 attempt, known as the first-pass effect, has correlated favorably with long-term outcomes. Pretreatment imagi...
Humans Tomography, X-Ray Computed Female Treatment Outcome Magnetic Resonance Imaging Aged Ischemic Stroke Male Endovascular Procedures Middle Aged Thrombectomy Deep Learning
View on PubMed DOI

Ensemble machine learning to predict futile recanalization after mechanical thrombectomy based on non-contrast CT imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Aug 6, 2024
OBJECTIVES: Despite successful recanalization after Mechanical Thrombectomy (MT), approximately 25 % of patients with Acute Ischemic Stroke (AIS) due to Large Vessel Occlusion (LVO) show unfavorable clinical outcomes, namely Futile Recanalization (FR...
Tomography, X-Ray Computed Clinical Decision-Making Female Risk Factors Aged Radiographic Image Interpretation, Computer-Assisted Infarction, Middle Cerebral Artery Thrombectomy Medical Futility Time Factors Treatment Outcome Predictive Value of Tests Ischemic Stroke Humans Aged, 80 and over Machine Learning Male Decision Support Techniques Middle Aged Retrospective Studies Risk Assessment
View on PubMed DOI

The stroke outcome optimization project: Acute ischemic strokes from a comprehensive stroke center.

Scientific data Aug 2, 2024
Stroke is a leading cause of disability, and Magnetic Resonance Imaging (MRI) is routinely acquired for acute stroke management. Publicly sharing these datasets can aid in the development of machine learning algorithms, particularly for lesion identi...
South Carolina Male Magnetic Resonance Imaging Ischemic Stroke Stroke Humans Machine Learning Female Aged
View on PubMed DOI

Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.

European radiology Jul 27, 2024
OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing ischemic changes in acute ischemic stroke using non-contrast computed tomography (NCCT), is often interpreted relying on expert experience and can vary...
Sensitivity and Specificity Male Middle Aged Deep Learning Humans Ischemic Stroke Prospective Studies Radiographic Image Interpretation, Computer-Assisted Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Aged Aged, 80 and over
View on PubMed DOI

Artificial intelligence/machine learning for neuroimaging to predict hemorrhagic transformation: Systematic review/meta-analysis.

Journal of neuroimaging : official journal of the American Society of Neuroimaging Jul 21, 2024
BACKGROUND AND PURPOSE: Early and reliable prediction of hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) is crucial for treatment decisions and early intervention. The purpose of this study was to conduct a systematic rev...
Machine Learning Cerebral Hemorrhage Humans Ischemic Stroke Neuroimaging Artificial Intelligence
View on PubMed DOI

Prognosticating global functional outcome in the recurrent ischemic stroke using baseline clinical and pre-clinical features: A machine learning study.

Journal of evaluation in clinical practice Jul 19, 2024
BACKGROUND AND PURPOSE: Recurrent ischemic stroke (RIS) induces additional functional limitations in patients. Prognosticating globally functional outcome (GFO) in RIS patients is thereby important to plan a suitable rehabilitation programme. This st...
Humans Machine Learning Prognosis Female Aged Recovery of Function Male Ischemic Stroke Middle Aged Recurrence Support Vector Machine Stroke Rehabilitation
View on PubMed DOI

Non-contrast CT radiomics-clinical machine learning model for futile recanalization after endovascular treatment in anterior circulation acute ischemic stroke.

BMC medical imaging Jul 19, 2024
OBJECTIVE: To establish a machine learning model based on radiomics and clinical features derived from non-contrast CT to predict futile recanalization (FR) in patients with anterior circulation acute ischemic stroke (AIS) undergoing endovascular tre...
Male Middle Aged Nomograms Ischemic Stroke Endovascular Procedures Medical Futility Tomography, X-Ray Computed Female Aged Radiomics Humans Machine Learning Prognosis Retrospective Studies
View on PubMed DOI
Popular Topics
Recent Journals