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Condition: Hemorrhagic Stroke
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Total 196 results found since Jan 2013.
Deep Transfer Learning for Automatic Prediction of Hemorrhagic Stroke on CT Images
In this study, we propose an automated transfer deep learning method that combines ResNet-50 and dense layer for accurate prediction of intracranial hemorrhage on NCCT brain images. A total of 1164 NCCT brain images were collected from 62 patients with hemorrhagic stroke from Kalinga Institute of Medical Science, Bhubaneswar and used for evaluating the model. The proposed model takes individual CT images as input and classifies them as hemorrhagic or normal. This deep transfer learning approach reached 99.6% accuracy, 99.7% specificity, and 99.4% sensitivity which are better results than that of ResNet-50 only. It is evide...
Source: Computational and Mathematical Methods in Medicine - April 26, 2022 Category: Statistics Authors: B Nageswara Rao Sudhansu Mohanty Kamal Sen U Rajendra Acharya Kang Hao Cheong Sukanta Sabut 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
Hospital Length of Stay and 30-Day Mortality Prediction in Stroke: A Machine Learning Analysis of 17,000 ICU Admissions in Brazil
ConclusionsHospital length of stay and 30-day mortality of patients admitted to the ICU with stroke were accurately predicted through machine learning methods, even in the absence of stroke-specific data, such as the National Institutes of Health Stroke Scale score or neuroimaging findings. The proposed methods using general intensive care databases may be used for resource use allocation planning and performance assessment of ICUs treating stroke. More detailed acute neurological and management data, as well as long-term functional outcomes, may improve the accuracy and applicability of future machine-learning-based prediction algorithms.
Source: Neurocritical Care - April 6, 2022 Category: Neurology Source Type: research
Data from New VOYAGER PAD Analyses at ACC.22 Reinforce Benefit of XARELTO ® (rivaroxaban) Plus Aspirin in Patients with Peripheral Artery Disease (PAD) and Various Co-Morbid Conditions
RARITAN, N.J., April 1, 2022 – The Janssen Pharmaceutical Companies of Johnson & Johnson today announced data from new analyses from the Phase 3 VOYAGER PAD clinical trial reinforcing the benefit of the XARELTO® (rivaroxaban) vascular dose (2.5 mg twice daily plus aspirin 100 mg once daily) in reducing severe vascular events in patients with PAD after lower-extremity revascularization (LER), a procedure that restores blood flow to the legs. Data from the two analyses demonstrate the role that the XARELTO® vascular dose plays in PAD patients with and without chronic kidney disease (CKD) and in PAD patients with and ...
Source: Johnson and Johnson - April 1, 2022 Category: Pharmaceuticals Tags: Innovation Source Type: news
The Gut Microbiota-Brain Axis in Acute Neurological Disease: Focus on Stroke
Rev Recent Clin Trials. 2022 Mar 21. doi: 10.2174/1574887117666220321155508. Online ahead of print.ABSTRACTThe gut microbiota is one of the great innovations of modern medicine. In the modern microbiota revolution era, more comprehensive and in-depth studies have been performed as regards the microbial gut communities and their impact on acute and chronic diseases, including those of the nervous system as acute neurological diseases. The microbiota has changed our knowledge of medical conditions; in particular, considering stroke (both ischemic and hemorrhagic), literature studies, experimental and clinical researches indi...
Source: Reviews on Recent Clinical Trials - March 23, 2022 Category: Cancer & Oncology Authors: Saviano Angela Gayani Gunawardena Zanza Christian Longhitano Yaroslava Migneco Alessio Candelli Marcello Franceschi Francesco Ojetti Veronica Source Type: research
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
Subarachnoid Hemorrhage Induces Sub-acute and Early Chronic Impairment in Learning and Memory in Mice
AbstractSubarachnoid hemorrhage (SAH) leads to significant long-term cognitive deficits, so-called the post-SAH syndrome. Existing neurological scales used to assess outcomes of SAH are focused on sensory-motor functions. To better evaluate short-term and chronic consequences of SAH, we explored and validated a battery of neurobehavioral tests to gauge the functional outcomes in mice after the circle of Willis perforation-induced SAH. The 18-point Garcia scale, applied up to 4 days, detected impairment only at 24-h time point and showed no significant difference between the Sham and SAH group. A decrease in locomotion wa...
Source: Translational Stroke Research - March 8, 2022 Category: Neurology Source Type: research
Radiomics-based prediction of hemorrhage expansion among patients with thrombolysis/thrombectomy related-hemorrhagic transformation using machine learning
CONCLUSIONS: The currently established NECT-based radiomic score is valuable in predicting hemorrhage expansion after HT among patients treated with reperfusion treatment after ischemic stroke, which may aid clinicians in determining patients with HT who are most likely to benefit from anti-expansion treatment.PMID:35173809 | PMC:PMC8842178 | DOI:10.1177/17562864211060029
Source: Adv Data - February 17, 2022 Category: Epidemiology Authors: Junfeng Liu Wendan Tao Zhetao Wang Xinyue Chen Bo Wu Ming Liu Source Type: research
A Magnetic Resonance Angiography-Based Study Comparing Machine Learning and Clinical Evaluation: Screening Intracranial Regions Associated with the Hemorrhagic Stroke of Adult Moyamoya Disease
Moyamoya disease (MMD) is a chronic occlusive cerebrovascular disease characterized by bilateral progressive steno-occlusive changes of unknown etiology at the distal portion of the internal carotid artery or proximal portion of the anterior arteries and middle cerebral arteries, accompanied by the presence of an abnormal vessel network (moyamoya vessels) at the base of the brain.1 The incidence and prevalence of MMD are increasing worldwide, which may indicate an increase in the number of MMD patients or an underestimation of the actual number of MMD patients in the past.
Source: Journal of Stroke and Cerebrovascular Diseases - February 17, 2022 Category: Neurology Authors: Hao-lin Yin, Yu Jiang, Wen-jun Huang, Shi-hong Li, Guang-wu Lin Source Type: research
Effects of Repetitive Peripheral Sensory Stimulation in the Subacute and Chronic Phases After Stroke: Study Protocol for a Pilot Randomized Trial
DiscussionThe results of this study are relevant to inform future clinical trials to tailor RPSS to patients more likely to benefit from this intervention.Trial RegistrationNCT03956407.
Source: Frontiers in Neurology - February 16, 2022 Category: Neurology Source Type: research
