About this Research Topic
Physicians have the opportunity and responsibility to track AI development in cerebrovascular and cardiovascular fields actively and selectively apply them to find concrete supporting tools to assist their clinical practice. The application of AI in the cerebrovascular and cardiovascular fields brings vast possibilities and provides new personalized care.
The cerebro-cardiovascular disease is the world’s leading cause of morbidity and mortality and the health industry’s most costly disease for treatment. However, despite recent advances in diagnosis and treatment, more effective and accessible ways to tackle cerebro-cardiovascular diseases remain discovered.
Artificial intelligence can make computers or machines learn to solve problems that require human effort. Advances in computing power have made it possible to analyze large amounts of data with consistency and accuracy quickly. This has enabled health care scientists to apply AI to massive, complex, heterogeneous data sets to improve decision-making, diagnosis, and treatment by detecting patient data patterns. The continuous development of AI techniques, mainly in the subdomains of machine learning and deep learning, has quickly attracted the attention of clinicians to create new integrated, reliable, and efficient methods for providing high-quality healthcare.
This special issue will present the advancement of AI technologies in handling cerebro-cardiovascular diseases, including noninvasive acquisition, accurate diagnosis, individualized therapy, early detection, intelligent screening, rehabilitation, etc.
Despite the significant advances in diagnosis and treatments, Cerebro-cardiovascular disease still represents the leading cause of morbidity and mortality worldwide. To improve and optimize these diseases’ outcomes, artificial intelligence techniques have the potential to radically change the way we practice cardiology, especially in imaging and Micro-nano-biosensors, offering us novel tools to interpret data and make clinical decisions. Furthermore, AI techniques such as machine learning and deep learning can also improve medical knowledge due to the increased volume and complexity of the data, unlocking clinically relevant information. Likewise, emerging communication and information technologies are becoming pivotal to creating a pervasive healthcare service through which elderly and chronic disease patients can receive medical care in their own homes, reducing hospitalizations and improving quality of life. In addition, these technologies can improve the prediction accuracy and treatment effect and alleviate both the financial and social burden.
This Research Topic describes the current state of AI and health electronics applied to cerebrovascular and cardiovascular medicine and provided physicians with their potential in wearable devices, biosensors, and medical imaging in clinical practice.
Potential topics include, but are not limited to:
• Sensors and health electronics for monitoring patients with cerebrovascular or cardiovascular diseases
• Association of cardiovascular structure and function with cerebrovascular changes and cognitive function
• The regulation of cardiovascular and cerebrovascular function at genetic, molecular, and cellular levels
• New technologies applied in cerebro-cardiovascular disease management and analysis
• Neural and cardiovascular rehabilitation
Keywords: Artificial intelligence, neurophysiological signals and images, biosensing and signal processing, wearable device, cerebro-cardiovascular health, identification and modeling, diagnosis and treatment, rehabilitation
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