AIMC Topic: Hematoma

Clear Filters Showing 11 to 20 of 55 articles

Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes.

Neurocritical care Aug 6, 2024
BACKGROUND: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning.
Glasgow Coma Scale Aged Male Middle Aged Outcome Assessment, Health Care Hematoma Cerebral Hemorrhage Seizures Machine Learning Phenotype Female Humans
View on PubMed DOI

A Deep Learning-Based Framework for Predicting Intracerebral Hematoma Expansion Using Head Non-contrast CT Scan.

Academic radiology Aug 5, 2024
RATIONALE AND OBJECTIVES: Hematoma expansion (HE) in intracerebral hemorrhage (ICH) is a critical factor affecting patient outcomes, yet effective clinical tools for predicting HE are currently lacking. We aim to develop a fully automated framework b...
Retrospective Studies Tomography, X-Ray Computed Female Humans Prospective Studies Middle Aged Aged Deep Learning Sensitivity and Specificity Cerebral Hemorrhage Male Hematoma
View on PubMed DOI

Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using a multimodal neural network.

Scientific reports Jul 16, 2024
Hematoma expansion occasionally occurs in patients with intracerebral hemorrhage (ICH), associating with poor outcome. Multimodal neural networks incorporating convolutional neural network (CNN) analysis of images and neural network analysis of tabul...
Neural Networks, Computer Machine Learning Retrospective Studies Humans Aged, 80 and over Male Middle Aged ROC Curve Tomography, X-Ray Computed Female Aged Cerebral Hemorrhage Hematoma
View on PubMed DOI

A Comparative Study of a Nomogram and Machine Learning Models in Predicting Early Hematoma Expansion in Hypertensive Intracerebral Hemorrhage.

Academic radiology Jun 26, 2024
RATIONALE AND OBJECTIVES: Early identification for hematoma expansion can help improve patient outcomes. Presently, there are many methods to predict hematoma expansion. This study compared a variety of models to find a model suitable for clinical pr...
Intracranial Hemorrhage, Hypertensive Middle Aged Nomograms Machine Learning Hematoma Female Tomography, X-Ray Computed Aged Male Humans
View on PubMed DOI

Machine learning for predicting hematoma expansion in spontaneous intracerebral hemorrhage: a systematic review and meta-analysis.

Neuroradiology Jun 12, 2024
PURPOSE: Early identification of hematoma enlargement and persistent hematoma expansion (HE) in patients with cerebral hemorrhage is increasingly crucial for determining clinical treatments. However, due to the lack of clinically effective tools, rad...
Predictive Value of Tests Hematoma Humans Machine Learning Tomography, X-Ray Computed Disease Progression Cerebral Hemorrhage
View on PubMed DOI

Predicting hematoma expansion using machine learning: An exploratory analysis of the ATACH 2 trial.

Journal of the neurological sciences May 12, 2024
INTRODUCTION: Hematoma expansion (HE) in patients with intracerebral hemorrhage (ICH) is a key predictor of poor prognosis and potentially amenable to treatment. This study aimed to build a classification model to predict HE in patients with ICH usin...
Disease Progression Cerebral Hemorrhage Antihypertensive Agents Hematoma Aged Male Humans Middle Aged Machine Learning Female
View on PubMed DOI

Application of deep learning and radiomics in the prediction of hematoma expansion in intracerebral hemorrhage: a fully automated hybrid approach.

Diagnostic and interventional radiology (Ankara, Turkey) Apr 24, 2024
PURPOSE: Spontaneous intracerebral hemorrhage (ICH) is the most severe form of stroke. The timely assessment of early hematoma enlargement and its proper treatment are of great significance in curbing the deterioration and improving the prognosis of ...
Radiomics Male Middle Aged Deep Learning Cerebral Hemorrhage Hematoma Tomography, X-Ray Computed Female Aged Humans Neural Networks, Computer
View on PubMed DOI

Prediction of Hematoma Expansion in Intracerebral Hemorrhage in 24 Hours by Machine Learning Algorithm.

World neurosurgery Feb 22, 2024
OBJECTIVE: The significance of noncontrast computer tomography (CT) image markers in predicting hematoma expansion (HE) following intracerebral hemorrhage (ICH) within different time intervals in the initial 24 hours after onset may be uncertain. Hen...
Disease Progression Time Factors Cerebral Hemorrhage Aged Male Humans Middle Aged Predictive Value of Tests Retrospective Studies Machine Learning Hematoma Tomography, X-Ray Computed Algorithms Female
View on PubMed DOI

Predicting hematoma expansion in acute spontaneous intracerebral hemorrhage: integrating clinical factors with a multitask deep learning model for non-contrast head CT.

Neuroradiology Feb 10, 2024
PURPOSE: To predict hematoma growth in intracerebral hemorrhage patients by combining clinical findings with non-contrast CT imaging features analyzed through deep learning.
Hematoma Retrospective Studies Tomography, X-Ray Computed Deep Learning Cerebral Hemorrhage Humans
View on PubMed DOI

Hematoma expansion prediction: still navigating the intersection of deep learning and radiomics.

European radiology Jan 22, 2024
Deep Learning Humans Magnetic Resonance Imaging Tomography, X-Ray Computed Hematoma Radiomics
View on PubMed DOI
Popular Topics
Recent Journals