AIMC Topic: Intracranial Hemorrhages
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Machine learning based classification of spontaneous intracranial hemorrhages using radiomics features.
Neuroradiology
Oct 5, 2024
PURPOSE: To assess the efficacy of radiomics features extracted from non-contrast computed tomography (NCCT) scans in differentiating multiple etiologies of spontaneous intracerebral hemorrhage (ICH).
Impact of a deep learning-based brain CT interpretation algorithm on clinical decision-making for intracranial hemorrhage in the emergency department.
Scientific reports
Sep 27, 2024
Intracranial hemorrhage is a critical emergency that requires prompt and accurate diagnosis in the emergency department (ED). Deep learning technology can assist in interpreting non-enhanced brain CT scans, but its real-world impact on clinical decis...
An Artificial Intelligence Algorithm Integrated into the Clinical Workflow Can Ensure High Quality Acute Intracranial Hemorrhage CT Diagnostic.
Clinical neuroradiology
Sep 26, 2024
PURPOSE: Intracranial hemorrhage (ICH) is a life-threatening condition requiring rapid diagnostic and therapeutic action. This study evaluates whether Artificial intelligence (AI) can provide high-quality ICH diagnostics and turnaround times suitable...
Prospective Evaluation of Artificial Intelligence Triage of Intracranial Hemorrhage on Noncontrast Head CT Examinations.
AJR. American journal of roentgenology
Sep 4, 2024
Retrospective studies evaluating artificial intelligence (AI) algorithms for intracranial hemorrhage (ICH) detection on noncontrast CT (NCCT) have shown promising results but lack prospective validation. The purpose of this article was to evaluate ...
Comment on 'Deep learning-assisted detection and segmentation of intracranial hemorrhage in noncontrast computed tomography scans of acute stroke patients: a systematic review and meta-analysis'.
International journal of surgery (London, England)
Sep 1, 2024
Potential strength and weakness of artificial intelligence integration in emergency radiology: a review of diagnostic utilizations and applications in patient care optimization.
Emergency radiology
Aug 27, 2024
Artificial intelligence (AI) and its recent increasing healthcare integration has created both new opportunities and challenges in the practice of radiology and medical imaging. Recent advancements in AI technology have allowed for more workplace eff...
Accuracy and time efficiency of a novel deep learning algorithm for Intracranial Hemorrhage detection in CT Scans.
La Radiologia medica
Aug 9, 2024
PURPOSE: To evaluate a deep learning-based pipeline using a Dense-UNet architecture for the assessment of acute intracranial hemorrhage (ICH) on non-contrast computed tomography (NCCT) head scans after traumatic brain injury (TBI).
Evaluating performance of a near-infrared-spectroscopy-based and machine-learning-powered bio-optical sensitivity parameters in identifying intracranial hemorrhages in TBI across different age-groups.
Brain injury
Jul 31, 2024
PRIMARY OBJECTIVE: To evaluate the accuracy of an innovative machine-learning-powered near-infrared spectroscopy (mNIRS)-based bio-optical sensitivity parameters, namely specific tissue optical index (STOI) and intracranial tissue optical index (ITOI...
Intracranial Hemorrhages
Age Factors
Brain Injuries, Traumatic
Double-Blind Method
Aged
Aged, 80 and over
Young Adult
Humans
Adult
Spectroscopy, Near-Infrared
Sensitivity and Specificity
Machine Learning
Adolescent
Cross-Sectional Studies
Prospective Studies
Child, Preschool
Male
Female
Child
Middle Aged
Diagnostic test accuracy of externally validated convolutional neural network (CNN) artificial intelligence (AI) models for emergency head CT scans - A systematic review.
International journal of medical informatics
Jun 13, 2024
BACKGROUND: The surge in emergency head CT imaging and artificial intelligence (AI) advancements, especially deep learning (DL) and convolutional neural networks (CNN), have accelerated the development of computer-aided diagnosis (CADx) for emergency...
Deep learning-assisted detection and segmentation of intracranial hemorrhage in noncontrast computed tomography scans of acute stroke patients: a systematic review and meta-analysis.
International journal of surgery (London, England)
Jun 1, 2024
BACKGROUND: Deep learning (DL)-assisted detection and segmentation of intracranial hemorrhage stroke in noncontrast computed tomography (NCCT) scans are well-established, but evidence on this topic is lacking.
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