AIMC Topic: Cerebrovascular Disorders

Clear Filters Showing 21 to 30 of 44 articles

Machine learning-based diagnosis and risk factor analysis of cardiocerebrovascular disease based on KNHANES.

Scientific reports Feb 10, 2022
The prevalence of cardiocerebrovascular disease (CVD) is continuously increasing, and it is the leading cause of human death. Since it is difficult for physicians to screen thousands of people, high-accuracy and interpretable methods need to be prese...
Cardiovascular Diseases Prevalence Nutrition Surveys Support Vector Machine Female Risk Factors Male Cerebrovascular Disorders Heart Disease Risk Factors Humans Machine Learning Republic of Korea
View on PubMed DOI

Deep Learning in the Management of Intracranial Aneurysms and Cerebrovascular Diseases: A Review of the Current Literature.

World neurosurgery Feb 5, 2022
Intracranial aneurysms are a common asymptomatic vascular pathology, the rupture of which is a devastating event with a significant risk of morbidity and mortality. Aneurysm detection and risk stratification before rupture events are, therefore, impe...
Deep Learning Cerebrovascular Disorders Moyamoya Disease Intracranial Aneurysm Humans Artificial Intelligence
View on PubMed DOI

Magnetic Resonance Image Feature Analysis under Deep Learning in Diagnosis of Neurological Rehabilitation in Patients with Cerebrovascular Diseases.

Contrast media & molecular imaging Oct 25, 2021
To explore the impact of magnetic resonance imaging (MRI) image features based on deep learning algorithms on the neurological rehabilitation of patients with cerebrovascular diseases, eighty patients with acute cerebrovascular disease were selected ...
Humans Magnetic Resonance Imaging Algorithms Cerebrovascular Disorders Deep Learning Neurological Rehabilitation Image Processing, Computer-Assisted
View on PubMed DOI

A disease-specific language representation model for cerebrovascular disease research.

Computer methods and programs in biomedicine Sep 30, 2021
BACKGROUND: Effectively utilizing disease-relevant text information from unstructured clinical notes for medical research presents many challenges. BERT (Bidirectional Encoder Representation from Transformers) related models such as BioBERT and Clini...
Humans Language Natural Language Processing Cerebrovascular Disorders
View on PubMed DOI

Large Vessel Occlusion Prediction in the Emergency Department with National Institutes of Health Stroke Scale Components: A Machine Learning Approach.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Aug 15, 2021
OBJECTIVE: To determine the feasibility of using a machine learning algorithm to screen for large vessel occlusions (LVO) in the Emergency Department (ED).
Prognosis Retrospective Studies Female Male Humans Machine Learning Disability Evaluation Middle Aged Functional Status Predictive Value of Tests Feasibility Studies Emergency Service, Hospital Cerebrovascular Disorders
View on PubMed DOI

Risk factors associated with major adverse cardiac and cerebrovascular events following percutaneous coronary intervention: a 10-year follow-up comparing random survival forest and Cox proportional-hazards model.

BMC cardiovascular disorders Jan 18, 2021
BACKGROUND: Due to the limited number of studies with long term follow-up of patients undergoing Percutaneous Coronary Intervention (PCI), we investigated the occurrence of Major Adverse Cardiac and Cerebrovascular Events (MACCE) during 10 years of f...
Iran Stents Cerebrovascular Disorders Heart Diseases Treatment Outcome Percutaneous Coronary Intervention Coronary Artery Disease Proportional Hazards Models Female Risk Factors Aged Male Middle Aged Risk Assessment Time Factors Humans Machine Learning Decision Support Techniques Retrospective Studies
View on PubMed DOI

Evaluation of Artificial Intelligence-Powered Identification of Large-Vessel Occlusions in a Comprehensive Stroke Center.

AJNR. American journal of neuroradiology Dec 31, 2020
BACKGROUND AND PURPOSE: Artificial intelligence algorithms have the potential to become an important diagnostic tool to optimize stroke workflow. Viz LVO is a medical product leveraging a convolutional neural network designed to detect large-vessel o...
Humans Neural Networks, Computer Stroke Cerebrovascular Disorders Image Interpretation, Computer-Assisted Computed Tomography Angiography Male Retrospective Studies Middle Aged Female Mobile Applications Aged Predictive Value of Tests
View on PubMed DOI

A Machine Learning Approach for Predicting Early Phase Postoperative Hypertension in Patients Undergoing Carotid Endarterectomy.

Annals of vascular surgery Jul 10, 2020
BACKGROUND: This study aimed to establish and validate a machine learning-based model for the prediction of early phase postoperative hypertension (EPOH) requiring the administration of intravenous vasodilators after carotid endarterectomy (CEA).
Administration, Intravenous Vasodilator Agents Cerebrovascular Circulation Carotid Stenosis Endarterectomy, Carotid Predictive Value of Tests Blood Pressure Antihypertensive Agents Time Factors Cerebrovascular Disorders Decision Support Techniques Adult Hypertension Databases, Factual Risk Factors Humans Male Retrospective Studies Treatment Outcome Aged Middle Aged Female Machine Learning Aged, 80 and over Risk Assessment
View on PubMed DOI

A novel computer-aided diagnosis system for the early detection of hypertension based on cerebrovascular alterations.

NeuroImage. Clinical Dec 2, 2019
Hypertension is a leading cause of mortality in the USA. While simple tools such as the sphygmomanometer are widely used to diagnose hypertension, they could not predict the disease before its onset. Clinical studies suggest that alterations in the s...
Neural Networks, Computer Magnetic Resonance Angiography Humans Cerebrovascular Disorders Diagnosis, Computer-Assisted Image Interpretation, Computer-Assisted Hypertension Early Diagnosis Pattern Recognition, Automated
View on PubMed DOI

Functional MRI in Conjunction with a Novel MRI-compatible Hand-induced Robotic Device to Evaluate Rehabilitation of Individuals Recovering from Hand Grip Deficits.

Journal of visualized experiments : JoVE Nov 23, 2019
Functional magnetic resonance imaging (fMRI) is a non-invasive magnetic resonance imaging technique that images brain activation in vivo, using endogenous deoxyhemoglobin as an endogenous contrast agent to detect changes in blood-level-dependent oxyg...
Robotics Hand Humans Cerebrovascular Disorders Magnetic Resonance Imaging Hand Strength
View on PubMed DOI
Popular Topics
Recent Journals