The inverse problem of inferring electrocardiogram (ECG) from photoplethysmogram (PPG) is an emerging research direction that combines the easy measurability of PPG and the rich clinical knowledge of ECG for long-term continuous cardiac monitoring.
Image matting is a long-standing problem in computer graphics and vision, mostly identified as the accurate estimation of the foreground in input images.
We analyze the latent connection between PPG and ECG as well as the CVDs-related features of PPG learned by the neural network, aiming at obtaining clinical insights from data.
The fundamental problem in treatment effect estimation from observational data is confounder identification and balancing.
Infectious keratitis is the most common entities of corneal diseases, in which pathogen grows in the cornea leading to inflammation and destruction of the corneal tissues.
In the field of information forensics, many emerging problems involve a critical step that estimates and tracks weak frequency components in noisy signals.
We present PyXtal, a new package based on the Python programming language, used to generate structures with specific symmetry and chemical compositions for both atomic and molecular systems.
Materials Science Computational Physics
Commercial cameras are promising contact-free sensors, and remote photoplethysmography (rPPG) have been studied to remotely monitor heart rate from face videos.
The study of grain boundary phase transitions is an emerging field until recently dominated by experiments.
This was done in order to improve the classification performance of these two classes of heartbeats by using different features and classification methods.
Ranked #2 on Heartbeat Classification on MIT-BIH AR