AIMC Topic: Cerebrovascular Disorders
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Automated Cerebrovascular Segmentation and Visualization of Intracranial Time-of-Flight Magnetic Resonance Angiography Based on Deep Learning.
Journal of imaging informatics in medicine
Aug 12, 2024
Time-of-flight magnetic resonance angiography (TOF-MRA) is a non-contrast technique used to visualize neurovascular. However, manual reconstruction of the volume render (VR) by radiologists is time-consuming and labor-intensive. Deep learning-based (...
Deep learning-based magnetic resonance imaging analysis for chronic cerebral hypoperfusion risk.
Medical physics
May 31, 2024
BACKGROUND: Chronic cerebral hypoperfusion (CCH) is a frequently encountered clinical condition that poses a diagnostic challenge due to its nonspecific symptoms.
Prediction and causal inference of cardiovascular and cerebrovascular diseases based on lifestyle questionnaires.
Scientific reports
May 7, 2024
Cardiovascular and cerebrovascular diseases (CCVD) are prominent mortality causes in Japan, necessitating effective preventative measures, early diagnosis, and treatment to mitigate their impact. A diagnostic model was developed to identify patients ...
Virtual hospital and artificial intelligence: a first step towards the application of an innovative health system for the care of rare cerebrovascular diseases.
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Nov 29, 2023
The development of virtual care options, including virtual hospital platforms, is rapidly changing the healthcare, mostly in the pandemic period, due to difficulties in in-person consultations. For this purpose, in 2020, a neurological Virtual Hospit...
Explainable prediction of daily hospitalizations for cerebrovascular disease using stacked ensemble learning.
BMC medical informatics and decision making
Apr 6, 2023
BACKGROUND: With the prevalence of cerebrovascular disease (CD) and the increasing strain on healthcare resources, forecasting the healthcare demands of cerebrovascular patients has significant implications for optimizing medical resources.
Application of deblur technology for improving the clarity of digital subtractive angiography.
Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
Dec 1, 2022
BACKGROUND: Digital subtraction angiography (DSA) is most commonly used in vessel disease examinations and treatments. We aimed to develop a novel deep learning-based method to deblur the large focal spot DSA images, so as to obtain a clearer and sha...
Transcranial Doppler analysis based on computer and artificial intelligence for acute cerebrovascular disease.
Mathematical biosciences and engineering : MBE
Nov 4, 2022
Cerebrovascular disease refers to damage to brain tissue caused by impaired intracranial blood circulation. It usually presents clinically as an acute nonfatal event and is characterized by high morbidity, disability, and mortality. Transcranial Dopp...
Deconstruction of Risk Prediction of Ischemic Cardiovascular and Cerebrovascular Diseases Based on Deep Learning.
Contrast media & molecular imaging
Sep 30, 2022
Over the years, with the widespread use of computer technology and the dramatic increase in electronic medical data, data-driven approaches to medical data analysis have emerged. However, the analysis of medical data remains challenging due to the mi...
Prediction of Metabolic Characteristics of Cardiovascular and Cerebrovascular Diseases Based on Convolutional Neural Network.
Computational and mathematical methods in medicine
Jul 27, 2022
As a typical disease, cardiovascular and cerebrovascular diseases cause great damage to the human body. In view of the problem that the existing models failed to describe and represent the characteristics of cardiovascular and cerebrovascular indicat...
Cognitive Impairment of Patient With Neurological Cerebrovascular Disease Using the Artificial Intelligence Technology Guided by MRI.
Frontiers in public health
Mar 3, 2022
This study was to explore the application of MRI based on artificial intelligence technology combined with neuropsychological assessment to the cognitive impairment of patients with neurological cerebrovascular diseases. A total of 176 patients were ...
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