Deep multiphysics: Coupling discrete multiphysics with machine learning to attain self-learning in-silico models replicating human physiology.

Journal: Artificial intelligence in medicine

PMID: 31521250

Abstract

OBJECTIVES: The objective of this study is to devise a modelling strategy for attaining in-silico models replicating human physiology and, in particular, the activity of the autonomic nervous system.

Authors

Alessio Alexiadis

School of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom. Electronic address: a.alexiadis@bham.ac.uk.

Keywords

Algorithms Autonomic Nervous System Computer Simulation Deep Learning Esophagus Feedback, Physiological Humans Machine Learning Models, Biological Peristalsis Physics Reinforcement, Psychology

External Resources

View on PubMed Access via DOI PubMed (31521250)

Deep multiphysics: Coupling discrete multiphysics with machine learning to attain self-learning in-silico models replicating human physiology.

Abstract

Authors

Keywords

External Resources

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