Ata uhi

Recent Advances in the Application of Mathematical and Computational Models in Biomedical Science and Engineering

This reprint highlights novel findings of state-of-the-art computational models based on multiscale, multiphysics, data-driven, artificial intelligence, and machine learning approaches in the field of bioengineering. Ten individual contributions from renowned research groups across the world have be...

Whakaahuatanga katoa

I tiakina i:
Hōputu: Online
Reo:Ingarihi
I whakaputaina: MDPI - Multidisciplinary Digital Publishing Institute 2024
Ngā marau:
peristaltic flow
non-zero Reynolds number
asymmetric channel
finite element method
porous media
design of experiments
holistic experimental design
integrated process model
optimal designs
process characterization
biopharmaceutical process validation
bioconvection flow
viscoelastic micropolar fluid
heat transfer
double diffusion
variable thermal conductivity
main protease (Mpro)
structure-based virtual screening
ZINC
in-house
ChemBridge database
molecular dynamics simulation
big data
data security
knight tour
steganography
wavelet transform
lossless compression
CT scan images
chest X-ray
transfer learning
COVID-19 detection
deep learning
surface electromyography (EMG)
motor unit
spatial distribution
EMG-force relation
biceps brachii
bio-heat transfer
light-tissue interaction
photothermal effect
acupuncture
acupoints
thermal therapy
computational modeling
SARS-CoV-2 prediction
feature selection
stochastic regression
neighbor embedding
sammon mapping
machine learning
pharmacokinetics
compartmental models
closed loop control
repeated drug administration
robust control
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
Urunga tuihono:ONIX_20240514_9783036593272_64
Ngā Tūtohu: Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
Whakarāpopototanga:This reprint highlights novel findings of state-of-the-art computational models based on multiscale, multiphysics, data-driven, artificial intelligence, and machine learning approaches in the field of bioengineering. Ten individual contributions from renowned research groups across the world have been published in this Special Issue.

Ngā tūemi rite