This article reviewed current advancements in mechanobiology (MB) and its applications to
investigate human tissue (soft and hard) using machine learning (ML) techniques. The study …

In recent years, Artificial intelligence (AI) has become ubiquitous, empowering various fields,
especially integrating artificial intelligence and traditional science (AI for Science: Artificial …

We extend EUCLID, a computational strategy for automated material model discovery and
identification, to linear viscoelasticity. For this case, we perform a priori model selection by …

The stiffness of soft biological tissues not only depends on the applied deformation, but also
on the deformation rate. To model this type of behavior, traditional approaches select a …

In vitro models of the human blood–brain barrier (BBB) are increasingly used to develop
therapeutics that can cross the BBB for treating diseases of the central nervous system. Here …

The constitutive behavior of polymeric materials is often modeled by finite linear viscoelastic
(FLV) or quasi-linear viscoelastic (QLV) models. These popular models are simplifications …

In contemporary elasticity theory, the strain–energy function predominantly relies on the first
invariant I 1 of the deformation tensor; a practice that has been influenced by models derived …

We propose an automated computational algorithm for simultaneous model selection and
parameter identification for the hyperelastic mechanical characterization of biological tissue …

Alzheimer's disease (AD) is a prevalent neurodegenerative disease and the world's primary
cause of dementia among the elderly population. The aggregation of toxic amyloid-beta (Aβ) …

Brain tissue is one of the most complex and softest tissues in the human body. Due to its
ultrasoft and biphasic nature, it is difficult to control the deformation state during …