Results 181 to 190 of about 890,275 (337)
Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare
Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu +10 more
wiley +1 more source
Data report about course on underlying cause-of-death coding (ICD-10): the case virtual learning environment of the Brazilian health system. [PDF]
Doreto AJ +13 more
europepmc +1 more source
ABSTRACT The lithium plating reaction in graphite electrodes acts as a root cause for the accelerated degradation and the internal short circuits in lithium‐ion batteries. Here, an electrochemical model based on multi‐scale microstructural images was established to identify lithium plating‐stripping processes, thereby supporting the predictive outcomes
Heng Huang +9 more
wiley +1 more source
Interculturality, public health and health education: data report based on the Virtual Learning Environment of the Brazilian Health System (AVASUS). [PDF]
da Cunha PS +12 more
europepmc +1 more source
Fostering teaching-learning through workplace based assessment in postgraduate chemical pathology residency program using virtual learning environment. [PDF]
Jafri L +10 more
europepmc +1 more source
This study proposes a piezoelectric interface modification strategy to amplify the piezoionic effect. The piezoelectric interface generates an intrinsic electric field, which not only drives rapid ion migration but also concentrates polarized ions on the interface. The flexible sensor delivers superior performance, such as a quick response rate, strong
Yanyu Chen +5 more
wiley +1 more source
Jordanian English language educators' perceived readiness for virtual learning environment. [PDF]
Madanat H +5 more
europepmc +1 more source
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang +6 more
wiley +1 more source

