AIMC Topic: Hemorrhagic Stroke

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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...
Humans Female Risk Factors Aged Aged, 80 and over Machine Learning Decision Support Techniques Prognosis Stroke Hemorrhagic Stroke Healthcare-Associated Pneumonia Predictive Value of Tests Ischemic Stroke Registries Male Middle Aged Risk Assessment
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Smartphone pupillometry with machine learning differentiates ischemic from hemorrhagic stroke: A pilot study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Dec 12, 2024
OBJECTIVES: Similarities between acute ischemic and hemorrhagic stroke make diagnosis and triage challenging. We studied a smartphone-based quantitative pupillometer for differentiation of acute ischemic and hemorrhagic stroke.
Female Reproducibility of Results Humans Middle Aged Machine Learning Case-Control Studies Pupil Pilot Projects Diagnostic Techniques, Ophthalmological Aged Smartphone Hemorrhagic Stroke Aged, 80 and over Diagnosis, Differential Reflex, Pupillary Male Predictive Value of Tests Ischemic Stroke
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Deep Transfer Learning for Automatic Prediction of Hemorrhagic Stroke on CT Images.

Computational and mathematical methods in medicine Apr 16, 2022
Intracerebral hemorrhage (ICH) is the most common type of hemorrhagic stroke which occurs due to ruptures of weakened blood vessel in brain tissue. It is a serious medical emergency issues that needs immediate treatment. Large numbers of noncontrast-...
Intracranial Hemorrhages Hemorrhagic Stroke Deep Learning Cerebral Hemorrhage Stroke Humans Tomography, X-Ray Computed
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Application of Deep Learning to Ischemic and Hemorrhagic Stroke Computed Tomography and Magnetic Resonance Imaging.

Seminars in ultrasound, CT, and MR Feb 11, 2022
Deep Learning (DL) algorithm holds great potential in the field of stroke imaging. It has been applied not only to the "downstream" side such as lesion detection, treatment decision making, and outcome prediction, but also to the "upstream" side for ...
Tomography, X-Ray Computed Stroke Hemorrhagic Stroke Deep Learning Magnetic Resonance Imaging
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A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning.

Scientific reports Dec 20, 2021
Stroke poses an immense public health burden and remains among the primary causes of death and disability worldwide. Emergent therapy is often precluded by late or indeterminate times of onset before initial clinical presentation. Rapid, mobile, safe...
Hemorrhagic Stroke Humans Neural Networks, Computer Area Under Curve Head Microwaves Reproducibility of Results Normal Distribution Algorithms Electromagnetic Fields Stochastic Processes Diagnosis, Computer-Assisted Brain Deep Learning Scattering, Radiation Computer Simulation ROC Curve
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Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion.

Stroke Sep 18, 2020
BACKGROUND AND PURPOSE: Clinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility ...
Ischemic Stroke Electroencephalography Stroke Ischemic Attack, Transient Hemorrhagic Stroke Middle Aged Deep Learning Logistic Models Humans Aged, 80 and over Neural Networks, Computer Sensitivity and Specificity Male Female Aged
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An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage.

Neuroimaging clinics of North America Sep 17, 2020
Hemorrhagic stroke is a medical emergency. Artificial intelligence techniques and algorithms may be used to automatically detect and quantitate intracranial hemorrhage in a semiautomated fashion. This article reviews the use of deep learning convolut...
Brain United States Triage Diagnostic Imaging Humans Image Interpretation, Computer-Assisted Artificial Intelligence Neuroimaging Machine Learning Hemorrhagic Stroke
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Machine learning-based prediction of 90-day prognosis and in-hospital mortality in hemorrhagic stroke patients.

Scientific reports May 9, 2025
This study aims to predict hemorrhagic stroke outcomes, including 90-day prognosis and in-hospital mortality, using machine learning models and SHapley Additive exPlanations (SHAP) analysis. Data were collected from a national Stroke Registry from Ja...
Male Middle Aged Severity of Illness Index Female Humans Hospital Mortality Stroke Aged Registries Machine Learning Hemorrhagic Stroke Aged, 80 and over Prognosis
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Advanced Machine Learning Models for Predicting Post-Thrombolysis Hemorrhagic Transformation in Acute Ischemic Stroke Patients: A Systematic Review and Meta-Analysis.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis Jan 1, 2024
Thrombolytic therapy is essential for acute ischemic stroke (AIS) management but poses a risk of hemorrhagic transformation (HT), necessitating accurate prediction to optimize patient care. A comprehensive search was conducted across PubMed, Web of...
Ischemic Stroke Thrombolytic Therapy Hemorrhagic Stroke Humans Machine Learning Risk Assessment
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