Reliability of ABC/2 volumetric estimation in spontaneous intracerebral hemorrhage for hematoma expansion prediction scores.

Introduction: Prediction scores for hematoma expansion in spontaneous intracerebral hemorrhage (ICH), such as the 9-point and BRAIN scores, were developed predominantly using planimetry to measure hematoma volume. In this study, we aim to investigate whether the ABC/2 formula, which is known to overestimate hematoma volume, can be reliably used as a substitute for planimetry in these prediction scores.

Patients And Methods: A total of 429 patients from four hospitals were retrospectively enrolled.

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

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 tabular data are known to show promising results in prediction and classification tasks. We aimed to develop a reliable multimodal neural network model that comprehensively analyzes CT images and clinical variables to predict hematoma expansion.

Machine learning prediction of hematoma expansion in acute intracerebral hemorrhage.

To examine whether machine learning (ML) approach can be used to predict hematoma expansion in acute intracerebral hemorrhage (ICH) with accuracy and widespread applicability, we applied ML algorithms to multicenter clinical data and CT findings on admission. Patients with acute ICH from three hospitals (n = 351) and those from another hospital (n = 71) were retrospectively assigned to the development and validation cohorts, respectively. To develop ML predictive models, the k-nearest neighbors (k-NN) algorithm, logistic regression, support vector machines (SVMs), random forests, and XGBoost were applied to the patient data in the development cohort.

Knowledge Learning of Replacement Judgment Using Word-of-mouth Data.

The pandemic caused by COVID-19 has also affected the camera industry, and various events have been cancelled. In addition, the recent improvement in the performance of cameras installed in smartphones has reduced the demand for replacement cameras, as it is easy to take pictures without carrying a camera. For customers, online word-of-mouth is what they refer to when purchasing a product.

Prolonged Cerebral Hyperperfusion and Subcortical Low Intensity on Fluid-Attenuated Inversion Recovery Images: Unusual Manifestation After Removal of Organized Chronic Subdural Hematoma.

Background: Cerebral hyperperfusion sometimes occurs after removal of chronic subdural hematoma (CSH) and usually resolves within a few days without any symptoms. Subcortical low intensity (SCLI) on fluid-attenuated inversion recovery (FLAIR) magnetic resonance images is rare and has been reported in some diseases other than CSH. A case of organized CSH who suffered prolonged neurologic deterioration, SCLI, and cerebral hyperperfusion postoperatively is described.

Cavernous Sinus Dural Arteriovenous Fistula Presenting with Intracerebral Hemorrhage Associated with Chronological Angiographic Demonstration of Disturbed Leptomeningeal Venous Drainage as the Sole Outflow Route.

Background: Cavernous sinus (CS) dural arteriovenous fistula (DAVF) rarely causes intracranial hemorrhage. The authors describe a case of CS DAVF presenting with intracranial hemorrhage, focusing on the findings in digital subtraction angiography (DSA) performed before and after the onset.

Case Description: An 80-year-old woman, diagnosed as Borden type 3 CS DAVF on DSA 2 years before, presented with subarachnoid hemorrhage and right temporal subcortical hemorrhage.