About this Research Topic
As the world's population ages, the prevalence of cerebrovascular diseases is rapidly rising. The cerebrovascular disease has a high rate of morbidity, mortality, disability and recurrence, all of which reduce patient quality of life and place an enormous financial burden on patients’ families and community. It has become an urgent challenge to tackle how to successfully reduce the incidence of cerebrovascular disease and improve the prognosis of cerebrovascular.
With the emergence of artificial intelligence (AI), the benefits and advancement of AI are embodied in many aspects of the medical field, including disease detection, auxiliary diagnosis and precision medicine. For example, the accuracy of brain imaging diagnostics has been increased by the extraction of imaging features using artificial intelligence techniques such as machine learning. Endovascular neurosurgery, which is one of the most common therapies for cerebrovascular diseases, has benefited significantly from the advancement of AI technology, which involves rapid differentiation of ischemic and hemorrhagic cerebrovascular diseases, risk assessment of intracranial aneurysm rupture, and rapid assessment of large vessel occlusion and ischemic penumbra by brain imaging.
In interventional neuroradiology, AI is an important measure for enhancing the quality of medical services for cerebrovascular diseases. It has proven that AI has exceptional clinical importance in the prevention, diagnosis, treatment and follow-up care of cerebrovascular diseases. The application of interventional neuroradiology robots, which has the advantages of high-precision operation, precise force perception, multimodal image data fusion, remote operation, remote consulting, and intelligent medical staff training, significantly enhances interventional surgery technology advancement.
This Research Topic seeks submissions that address the theoretical and technical complexities of evolutionary transformation from clinical systems to artificial intelligence technology in interventional neuroradiology, as well as the latest developments in modeling, design, analysis, deployment, and therapeutic testing of human assistive artificial intelligence medical applications. All aspects of clinically inspired artificial intelligence in interventional neuroradiology are welcome.
Potential topics include but are not limited to the following:
- Application of intelligent assistant decision-making system in interventional neuroradiology for cerebrovascular disease (Including but not limited to intelligent diagnostic and risk prediction)
- Application of rehabilitation engineering robotics and medical robotics in interventional neuroradiology for cerebrovascular disease
- Automation, control systems, simulation techniques, transformation technology and control applications in interventional neuroradiology for cerebrovascular disease
- Remote consulting and robotic operation in interventional neuroradiology for the treatment of cerebrovascular disease
- Intelligent training and assessment of medical staff in interventional neuroradiology for the treatment of cerebrovascular disease
- Intelligent techniques that make the medical staff more convenient and friendly during the treatment of cerebrovascular disease.
With the emergence of artificial intelligence (AI), the benefits and advancement of AI are embodied in many aspects of the medical field, including disease detection, auxiliary diagnosis and precision medicine. For example, the accuracy of brain imaging diagnostics has been increased by the extraction of imaging features using artificial intelligence techniques such as machine learning. Endovascular neurosurgery, which is one of the most common therapies for cerebrovascular diseases, has benefited significantly from the advancement of AI technology, which involves rapid differentiation of ischemic and hemorrhagic cerebrovascular diseases, risk assessment of intracranial aneurysm rupture, and rapid assessment of large vessel occlusion and ischemic penumbra by brain imaging.
In interventional neuroradiology, AI is an important measure for enhancing the quality of medical services for cerebrovascular diseases. It has proven that AI has exceptional clinical importance in the prevention, diagnosis, treatment and follow-up care of cerebrovascular diseases. The application of interventional neuroradiology robots, which has the advantages of high-precision operation, precise force perception, multimodal image data fusion, remote operation, remote consulting, and intelligent medical staff training, significantly enhances interventional surgery technology advancement.
This Research Topic seeks submissions that address the theoretical and technical complexities of evolutionary transformation from clinical systems to artificial intelligence technology in interventional neuroradiology, as well as the latest developments in modeling, design, analysis, deployment, and therapeutic testing of human assistive artificial intelligence medical applications. All aspects of clinically inspired artificial intelligence in interventional neuroradiology are welcome.
Potential topics include but are not limited to the following:
- Application of intelligent assistant decision-making system in interventional neuroradiology for cerebrovascular disease (Including but not limited to intelligent diagnostic and risk prediction)
- Application of rehabilitation engineering robotics and medical robotics in interventional neuroradiology for cerebrovascular disease
- Automation, control systems, simulation techniques, transformation technology and control applications in interventional neuroradiology for cerebrovascular disease
- Remote consulting and robotic operation in interventional neuroradiology for the treatment of cerebrovascular disease
- Intelligent training and assessment of medical staff in interventional neuroradiology for the treatment of cerebrovascular disease
- Intelligent techniques that make the medical staff more convenient and friendly during the treatment of cerebrovascular disease.
Keywords: Artificial Intelligence, Interventional Neuroradiology, Cerebrovascular Disease, Endovascular Medical Robotics, Brain Imaging Diagnostics
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
