The properties of biomedical intelligent polymer materials can be changed obviously when there is a little physical or chemical change in external condition. They are in the forms of solids, solutions and polymers on the surface of carrier, including aqueous solution of hydrophilic polymers, cross-linking hydrophilic polymers (i.e. hydrogels) and the polymers on the surface of carrier. In this paper are reviewed the progress in researches and the application of biomedical intelligent polymer materials.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Demographic-Based Personalized Left Ventricular Hypertrophy Thresholds for Hypertrophic Cardiomyopathy Diagnosis.
J Am Coll Cardiol
December 2024
Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, United Kingdom; Institute of Cardiovascular Science, University College London, London, United Kingdom.
Background: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death. Current diagnosis emphasizes the detection of left ventricular hypertrophy (LVH) using a fixed threshold of ≥15-mm maximum wall thickness (MWT). This study proposes a method that considers individual demographics to adjust LVH thresholds as an alternative to a 1-size-fits-all approach.
View Article and Find Full Text PDFWolbachia-Based Approaches to Controlling Mosquito-Borne Viral Threats: Innovations, AI Integration, and Future Directions in the Context of Climate Change.
Viruses
November 2024
Department of Sciences and Technologies for Sustainable Development and One Health, Universita Campus Bio-Medico di Roma, 00128 Rome, Italy.
Wolbachia-based mosquito control strategies have gained significant attention as a sustainable approach to reduce the transmission of vector-borne diseases such as dengue, Zika, and chikungunya. These endosymbiotic bacteria can limit the ability of mosquitoes to transmit pathogens, offering a promising alternative to traditional chemical-based interventions. With the growing impact of climate change on mosquito population dynamics and disease transmission, Wolbachia interventions represent an adaptable and resilient strategy for mitigating the public health burden of vector-borne diseases.
View Article and Find Full Text PDFVaccine Strategies Against RNA Viruses: Current Advances and Future Directions.
Vaccines (Basel)
November 2024
Research Center for Emerging Viral Infections, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan.
The development of vaccines against RNA viruses has undergone a rapid evolution in recent years, particularly driven by the COVID-19 pandemic. This review examines the key roles that RNA viruses, with their high mutation rates and zoonotic potential, play in fostering vaccine innovation. We also discuss both traditional and modern vaccine platforms and the impact of new technologies, such as artificial intelligence, on optimizing immunization strategies.
View Article and Find Full Text PDFUAV Trajectory Control and Power Optimization for Low-Latency C-V2X Communications in a Federated Learning Environment.
Sensors (Basel)
December 2024
Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON M5B2K3, Canada.
Unmanned aerial vehicle (UAV)-enabled vehicular communications in the sixth generation (6G) are characterized by line-of-sight (LoS) and dynamically varying channel conditions. However, the presence of obstacles in the LoS path leads to shadowed fading environments. In UAV-assisted cellular vehicle-to-everything (C-V2X) communication, vehicle and UAV mobility and shadowing adversely impact latency and throughput.
View Article and Find Full Text PDFImage Synthesis in Nuclear Medicine Imaging with Deep Learning: A Review.
Sensors (Basel)
December 2024
Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju 61186, Jeollanam-do, Republic of Korea.
Nuclear medicine imaging (NMI) is essential for the diagnosis and sensing of various diseases; however, challenges persist regarding image quality and accessibility during NMI-based treatment. This paper reviews the use of deep learning methods for generating synthetic nuclear medicine images, aimed at improving the interpretability and utility of nuclear medicine protocols. We discuss advanced image generation algorithms designed to recover details from low-dose scans, uncover information hidden by specific radiopharmaceutical properties, and enhance the sensing of physiological processes.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!