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Condition: Hemorrhagic Stroke
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Total 196 results found since Jan 2013.

Computational Approaches for Acute Traumatic Brain Injury Image Recognition
In recent years, there have been major advances in deep learning algorithms for image recognition in traumatic brain injury (TBI). Interest in this area has increased due to the potential for greater objectivity, reduced interpretation times and, ultimately, higher accuracy. Triage algorithms that can re-order radiological reading queues have been developed, using classification to prioritize exams with suspected critical findings. Localization models move a step further to capture more granular information such as the location and, in some cases, size and subtype, of intracranial hematomas that could aid in neurosurgical ...
Source: Frontiers in Neurology - March 9, 2022 Category: Neurology Source Type: research

Machine Learning-Based Perihematomal Tissue Features to Predict Clinical Outcome after Spontaneous Intracerebral Hemorrhage
To explore whether radiomic features of perihematomal tissue can improve the forecasting accuracy for the prognosis of patients with an intracerebral hemorrhage (ICH).
Source: Journal of Stroke and Cerebrovascular Diseases - April 11, 2022 Category: Neurology Authors: Xin Qi, Guorui Hu, Haiyan Sun, Zhigeng Chen, Chao Yang Source Type: research

Pilot Report for Intracranial Hemorrhage Detection with Deep Learning Implanted Head Computed Tomography Images at Emergency Department
AbstractHemorrhagic stroke is a serious clinical condition that requires timely diagnosis. An artificial intelligence algorithm system called DeepCT can identify hemorrhagic lesions rapidly from non-contrast head computed tomography (NCCT) images and has received regulatory clearance.  A non-controlled retrospective pilot clinical trial was conducted. Patients who received NCCT at the emergency department (ED) of Kaohsiung Veteran General Hospital were collected. From 2020 January-1st to April-30th, the physicians read NCCT images without DeepCT. From 2020May-1st to August-31st, the physicians were assisted by DeepCT. The...
Source: Journal of Medical Systems - June 8, 2022 Category: Information Technology Source Type: research

A deep learning based automatic system for intracranial aneurysms diagnosis on Three-Dimensional digital subtraction angiographic images
CONCLUSIONS: We have demonstrated that a comprehensive system can automatically detect, measure morphology and report aneurysm location of aneurysms without human intervention. This can be a potential tool for the diagnosis of intracranial aneurysms, improving radiologists' performance and reducing their workload. This article is protected by copyright. All rights reserved.PMID:35792717 | DOI:10.1002/mp.15846
Source: Health Physics - July 6, 2022 Category: Physics Authors: Chubin Ou Yi Qian Winston Chong Xiaoxi Hou Mingzi Zhang Xin Zhang Weixin Si Chuan-Zhi Duan Source Type: research

Pilot Report for Intracranial Hemorrhage Detection with Deep Learning Implanted Head Computed Tomography Images at Emergency Department
AbstractHemorrhagic stroke is a serious clinical condition that requires timely diagnosis. An artificial intelligence algorithm system called DeepCT can identify hemorrhagic lesions rapidly from non-contrast head computed tomography (NCCT) images and has received regulatory clearance.  A non-controlled retrospective pilot clinical trial was conducted. Patients who received NCCT at the emergency department (ED) of Kaohsiung Veteran General Hospital were collected. From 2020 January-1st to April-30th, the physicians read NCCT images without DeepCT. From 2020May-1st to August-31st, the physicians were assisted by DeepCT. The...
Source: Journal of Medical Systems - June 8, 2022 Category: Information Technology Source Type: research

Prediction of bleb formation in intracranial aneurysms using machine learning models based on aneurysm hemodynamics, geometry, location, and patient population
Conclusions Based on the premise that aneurysm characteristics prior to bleb formation resemble those derived from vascular reconstructions with their blebs virtually removed, machine learning models can identify aneurysms prone to bleb development with good accuracy. Pending further validation with longitudinal data, these models may prove valuable for assessing the propensity of IAs to progress to vulnerable states and potentially rupturing.
Source: Journal of NeuroInterventional Surgery - September 14, 2022 Category: Neurosurgery Authors: Salimi Ashkezari, S. F., Mut, F., Slawski, M., Cheng, B., Yu, A. K., White, T. G., Woo, H. H., Koch, M. J., Amin-Hanjani, S., Charbel, F. T., Rezai Jahromi, B., Niemelä, M., Koivisto, T., Frosen, J., Tobe, Y., Maiti, S., Robertson, A. M., Cebral, Tags: Hemorrhagic stroke Source Type: research

Brain PET and Cerebrovascular Disease
Cerebrovascular disease encompasses a broad spectrum of diseases such as stroke, hemorrhage, and cognitive decline associated with vascular narrowing, obstruction, rupture, and inflammation, among other issues. Recent advances in hardware and software have led to improvements in brain PET. Although still in its infancy, machine learning using convolutional neural networks is gaining traction in this area, often with a focus on providing high-quality images with reduced noise using a shorter acquisition time or less radiation exposure for the patient.
Source: PET Clinics - October 27, 2022 Category: Radiology Authors: Katarina Chiam, Louis Lee, Phillip H. Kuo, Vincent C. Gaudet, Sandra E. Black, Katherine A. Zukotynski Source Type: research

Specific signature biomarkers highlight the potential mechanisms of circulating neutrophils in aneurysmal subarachnoid hemorrhage
Conclusion: We identified core regulatory genes influencing the transcription profiles of circulating neutrophils after the rupture of intracranial aneurysms using bioinformatics analysis and machine learning algorithms. This study provides new insight into the mechanism of peripheral immune response and inflammation after aSAH.
Source: Frontiers in Pharmacology - November 10, 2022 Category: Drugs & Pharmacology Source Type: research

Is This Primary Exertional Headache?
Discussion Commonly occurring primary headaches include tension, cluster and migraine headaches. “Other primary headaches” are often situational. Patients can have more than 1 type of these “other” headaches along with more common headaches. Other primary headaches as a group tend to be self-limited with long remission periods. Some other primary headaches include: Thunderclap headache Explosive sudden onset with maximum intensity in less 1 minute and resolution within 5 minutes usually 43/100,000 persons in adults Primary or secondary Secondary causes include intracranial hemorrhage, stroke, thro...
Source: PediatricEducation.org - November 21, 2022 Category: Pediatrics Authors: Pediatric Education Tags: Uncategorized Source Type: news

Magnetic Targeting Nanocarriers Combined with Focusing Ultrasound for Enhanced Intracerebral Hemorrhage Therapy
A magnetic targeting nanocarrier loaded with a peroxisome proliferator-activated receptor gamma agonist (15d-PGJ2-MNPs) is magnetically targeted to the area of the hematoma with the subsequent application of focusing ultrasound for alleviating brain injury, accelerating hematoma clearance, attenuating neuroinflammation, and reducing the brain edema in the intracerebral hemorrhage mouse model. AbstractIntracerebral hemorrhage (ICH) remains a significant cause of morbidity and mortality around the world, and surgery is still the most direct and effective way to remove ICH. However, the potential risks brought by surgery, suc...
Source: Small - January 27, 2023 Category: Nanotechnology Authors: Tianyi Wang, Huali Lei, Xiang Li, Nailin Yang, Cheng Ma, Guangqiang Li, Xiang Gao, Jun Ge, Zhuang Liu, Liang Cheng, Gang Chen Tags: Research Article Source Type: research

Alpha-Asarone Ameliorates Neurological Dysfunction of Subarachnoid Hemorrhagic Rats in Both Acute and Recovery Phases via Regulating the CaMKII-Dependent Pathways
AbstractEarly brain injury (EBI) is the leading cause of poor prognosis for patients suffering from subarachnoid hemorrhage (SAH), particularly learning and memory deficits in the repair phase. A recent report has involved calcium/calmodulin-dependent protein kinase II (CaMKII) in the pathophysiological process underlying SAH-induced EBI. Alpha-asarone (ASA), a major compound isolated from the Chinese medicinal herbAcorus tatarinowii Schott, was proven to reduce secondary brain injury by decreasing CaMKII over-phosphorylation in rats ’ model of intracerebral hemorrhage in our previous report. However, the effect of ASA o...
Source: Translational Stroke Research - February 13, 2023 Category: Neurology Source Type: research

What Sub-Saharan African Nations Can Teach the U.S. About Black Maternal Health
While poor maternal outcomes among Black women in the U.S. is not new, improving it is imperative. U.S. policymakers can look to sub-Saharan Africa for guidance on reversing this trend. Credit: Ernest Ankomah/IPSBy Ifeanyi NsoforABUJA, Jun 2 2023 (IPS) New research shows that Black mothers in the United States disproportionately live in counties with higher maternal vulnerability and face greater risk of preterm death for the fetus, greater risk of low birth weight for a baby, and a higher number of maternal deaths. While poor maternal outcomes among Black women in the U.S. is not new, improving it is imperative. U.S. poli...
Source: IPS Inter Press Service - Health - June 2, 2023 Category: International Medicine & Public Health Authors: Ifeanyi Nsofor Tags: Africa Gender Headlines Health Inequality North America Poverty & SDGs Maternal Health Source Type: news

CT Angiography Radiomics Combining Traditional Risk Factors to Predict Brain Arteriovenous Malformation Rupture: a Machine Learning, Multicenter Study
This study aimed to develop a machine learning model for predicting brain arteriovenous malformation (bAVM) rupture using a combination of traditional risk factors and radiomics features. This multicenter retrospective study enrolled 586 patients with unruptured bAVMs from 2010 to 2020. All patients were grouped into the hemorrhage (n = 368) and non-hemorrhage (n = 218) groups. The bAVM nidus were segmented on CT angiography images using Slicer software, and radiomic features were extracted using Pyradiomics. The dataset included a training set and an independent testing set. The machine learning model was developed on the...
Source: Translational Stroke Research - June 13, 2023 Category: Neurology Source Type: research

Deep-Learning-Enabled Microwave-Induced Thermoacoustic Tomography Based on ResAttU-Net for Transcranial Brain Hemorrhage Detection
Conclusion: The proposed ResAttU-Net-based DL-MITAT method is promising for mitigating the acoustic inhomogeneity issue and performing transcranial brain hemorrhage detection. Significance: This work provides a novel ResAttU-Net-based DL-MITAT paradigm and paves a compelling route for transcranial brain hemorrhage detection as well as other transcranial brain imaging applications.
Source: IEEE Transactions on Biomedical Engineering - July 21, 2023 Category: Biomedical Engineering Source Type: research

Corrigendum: Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis
Source: Frontiers in Neurology - July 27, 2023 Category: Neurology Source Type: research