AIMC Topic: Models, Biological

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Soft robotic brittle star shows the influence of mass distribution on underwater walking.

Bioinspiration & biomimetics
Most walking organisms tend to have relatively light limbs and heavy bodies in order to facilitate rapid limb motion. However, the limbs of brittle stars (Class Ophiuroidea) are primarily comprised of dense skeletal elements, with potentially much hi...

A Hybrid ODE-NN Framework for Modeling Incomplete Physiological Systems.

IEEE transactions on bio-medical engineering
This paper proposes a method to learn approximations of missing Ordinary Differential Equations (ODEs) and states in physiological models where knowledge of the system's relevant states and dynamics is incomplete. The proposed method augments known O...

NEXT-FBA: A hybrid stoichiometric/data-driven approach to improve intracellular flux predictions.

Metabolic engineering
Genome-scale metabolic models (GEMs) have been widely utilized to understand cellular metabolism. The application of GEMs has been advanced by computational methods that enable the prediction and analysis of intracellular metabolic states. However, t...

Design and application of ISSA-BP neural network model for predicting soft tissue relaxation force.

Acta of bioengineering and biomechanics
: Accurate biomechanical modeling is crucial for enhancing the realism of virtual surgical training. This study addressed the computational cost and complexity associated with traditional viscoelastic models by incorporating neural network algorithms...

A Learnable Prior Improves Inverse Tumor Growth Modeling.

IEEE transactions on medical imaging
Biophysical modeling, particularly involving partial differential equations (PDEs), offers significant potential for tailoring disease treatment protocols to individual patients. However, the inverse problem-solving aspect of these models presents a ...

Biological age prediction using a DNN model based on pathways of steroidogenesis.

Science advances
Aging involves the progressive accumulation of cellular damage, leading to systemic decline and age-related diseases. Despite advances in medicine, accurately predicting biological age (BA) remains challenging due to the complexity of aging processes...

Machine learning-derived diagnostic model of epithelial ovarian cancer based on gut microbiome signatures.

Journal of translational medicine
BACKGROUND: Prior studies have elucidated that alterations in gut microbiota are associated with a spectrum of tumors and metabolic disorders. However, the diagnostic value of gut microbiota in epithelial ovarian cancer remains insufficiently investi...

Control of medical digital twins with artificial neural networks.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
The objective of precision medicine is to tailor interventions to an individual patient's unique characteristics. A key technology for this purpose involves medical digital twins, computational models of human biology that can be personalized and dyn...

Predicting the diversity of photosynthetic light-harvesting using thermodynamics and machine learning.

PLoS computational biology
Oxygenic photosynthesis is responsible for nearly all biomass production on Earth, and may have been a prerequisite for establishing a complex biosphere rich in multicellular life. Life on Earth has evolved to perform photosynthesis in a wide range o...

RSM and AI based machine learning for quality by design development of rivaroxaban push-pull osmotic tablets and its PBPK modeling.

Scientific reports
The study is based on applying Artificial Neural Network (ANN) based machine learning and Response Surface Methodology (RSM) as simultaneous bivariate approaches in developing controlled-release rivaroxaban (RVX) osmotic tablets. The influence of dif...