When AI meets additive manufacturing: Challenges and emerging opportunities for human-centered products development
Nowadays, additive manufacturing (AM) has been increasingly leveraged to produce human-
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
In-situ point cloud fusion for layer-wise monitoring of additive manufacturing
Additive manufacturing (AM) has received an increasing attention in the manufacturing
sector, owing to its high-level design freedom and enhanced capability to produce parts with …
sector, owing to its high-level design freedom and enhanced capability to produce parts with …
Hierarchical deep learning with Generative Adversarial Network for automatic cardiac diagnosis from ECG signals
Cardiac disease is the leading cause of death in the US. Accurate heart disease detection is
critical to timely medical treatment to save patients' lives. Routine use of the …
critical to timely medical treatment to save patients' lives. Routine use of the …
Healthcare in Asymmetrically Smart Future Environments: Applications, Challenges and Open Problems
The Internet of Medical Things (IoMT) offers promising ways to meet healthcare needs of
patients recovering in their own homes and other environments. Interconnected and resilient …
patients recovering in their own homes and other environments. Interconnected and resilient …
Digital twinning and optimization of manufacturing process flows
The new wave of Industry 4.0 is transforming manufacturing factories into data-rich
environments. This provides an unprecedented opportunity to feed large amounts of sensing …
environments. This provides an unprecedented opportunity to feed large amounts of sensing …
Tensor-based ECG anomaly detection toward cardiac monitoring in the internet of health things
Advanced heart monitors, especially those enabled by the Internet of Health Things (IoHT),
provide a great opportunity for continuous collection of the electrocardiogram (ECG), which …
provide a great opportunity for continuous collection of the electrocardiogram (ECG), which …
DG-ECG: Multi-stream deep graph learning for the recognition of disease-altered patterns in electrocardiogram
Abstract Representation learning of electrocardiogram (ECG) has been an active research
field for the automated detection of cardiac disease. In addition to extracting time and …
field for the automated detection of cardiac disease. In addition to extracting time and …
A comprehensive secure system enabling healthcare 5.0 using federated learning, intrusion detection and blockchain
J Almalki, SM Alshahrani, NA Khan - PeerJ Computer Science, 2024 - peerj.com
Recently, the use of the Internet of Medical Things (IoMT) has gained popularity across
various sections of the health sector. The historical security risks of IoMT devices themselves …
various sections of the health sector. The historical security risks of IoMT devices themselves …
Exploring factors influencing the adoption of mobile Healthcare Technologies: perspectives from Designers, consultants and users' preferences
S Namirad, M Deiranlou, SM Sajadi - American Journal of Business, 2023 - emerald.com
Purpose Today, the use of smart technologies in healthcare systems is experiencing
exponential growth, and the future of healthcare is seemingly closely intertwined with such …
exponential growth, and the future of healthcare is seemingly closely intertwined with such …
A review on statistical process control in healthcare: data-driven monitoring schemes
BE Pérez-Benítez, VG Tercero-Gómez… - IEEe …, 2023 - ieeexplore.ieee.org
In recent years, the adoption of statistical process monitoring (SPM) techniques in
healthcare has been successful. For instance, biosurveillance and biosignal monitoring …
healthcare has been successful. For instance, biosurveillance and biosignal monitoring …