AIMC Topic: Computer Simulation

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Toward artificial intelligence in dental prosthesis planning - a preliminary in-silico feasibility study.

BMC oral health
BACKGROUND: Dental prosthesis planning is a multi-faceted and nuanced process of conceiving individual treatment plans based on dental findings and in line with established treatment guidelines. The aim of this study was to assess whether an artifici...

Poliomyelitis dynamics with fractional order derivatives and deep neural networks.

Scientific reports
This paper presents a comprehensive study of poliomyelitis transmission dynamics using two fractional-order models that incorporate the Atangana--Baleanu derivatives in the Caputo sense (ABC). The model includes critical epidemiological features, inc...

Current state and open problems in universal differential equations for systems biology.

NPJ systems biology and applications
Universal Differential Equations (UDEs) combine mechanistic differential equations with data-driven artificial neural networks, forming a flexible framework for modelling complex biological systems. This hybrid approach leverages prior knowledge and ...

Hip, knee, and ankle joint forces during exoskeletal-assisted walking: Comparison of approaches to simulate human-robot interactions.

PloS one
The overall goal of this study was to develop a computational framework to quantify hip, knee, and ankle joint forces during exoskeletal-assisted walking (EAW) in the ReWalk P6.0, an FDA-approved lower-extremity exoskeleton. The first objective was t...

A multi-strategy enhanced secretary bird optimization algorithm for high-precision inverse kinematics in robotic arms.

PloS one
The assembly of pyrotechnic grain demands high precision and stability in robotic arm motion control due to the small shell apertures and stringent assembly accuracy requirements. Inverse kinematics is a core technology in robotic arm motion control....

Latent variable sequence identification for cognitive models with neural network estimators.

Behavior research methods
Extracting time-varying latent variables from computational cognitive models plays a key role in uncovering the dynamic cognitive processes that drive behaviors. However, existing methods are limited to inferring latent variable sequences in a relati...

Cox proportional hazards model with Bayesian neural network for survival prediction.

Scientific reports
Survival analysis plays a crucial aspect in medical research and other domains where understanding the time-to-events is paramount. In this study, we present a novel approach for estimating survival outcomes that combines Bayesian neural networks wit...

Leveraging agent-based models and deep reinforcement learning to predict taxis in cell migration.

NPJ systems biology and applications
We present a novel computational framework that combines Agent-Based Modeling (ABM) with Reinforcement Learning (RL) using the Double Deep Q-Network (DDQN) algorithm to determine cellular behavior in response to environmental signals. With this appro...

Structural and functional analysis of the accessory gene regulators of Staphylococcus aureus and Staphylococcus epidermidis: an in Silico approach.

BMC microbiology
BACKGROUND: Staphylococcus aureus and Staphylococcus epidermidis are tenacious pathogens that cause toxic shock syndrome. Accessory gene regulator (Agr) of Staphylococcus sp. controls the expression of multiple genes that encode virulence properties....

Accurate modeling and simulation of the effect of bacterial growth on the pH of culture media using artificial intelligence approaches.

Scientific reports
This research investigates the impact of bacterial growth on the pH of culture media, emphasizing its significance in microbiological and biotechnological applications. A range of sophisticated artificial intelligence methods, including One-Dimension...