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

doi:10.3390/books978-3-0365-9326-5

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https://mdpi.com/books/pdfview/book/8617

Contributor(s)

Singh, Sundeep (editor)

Melnik, Roderick (editor)

Pueyo, Esther (editor)

Language

English

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Résumé

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.

URI

https://directory.doabooks.org/handle/20.500.12854/137462

Keywords

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