AIMC Topic: Models, Biological

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Gait-CNN-ViT: Multi-Model Gait Recognition with Convolutional Neural Networks and Vision Transformer.

Sensors (Basel, Switzerland)
Gait recognition, the task of identifying an individual based on their unique walking style, can be difficult because walking styles can be influenced by external factors such as clothing, viewing angle, and carrying conditions. To address these chal...

Dynamic turning and running of a hexapod robot using a separated and laterally arranged two-leg model.

Bioinspiration & biomimetics
We report on the development of separated and laterally arranged two-leg (SLTL) models with/without differentiated leg properties and their use as the dynamic running and turning templates for a hexapod robot. The laterally arranged two-leg morpholog...

A pharmacokinetic-pharmacodynamic model based on the SSA-1DCNN-Attention network and the semicompartment method.

Biotechnology & genetic engineering reviews
To solve the problem of inaccurate prediction caused by the lack of representativeness of samples due to the small sample size of the collected clinical data when using machine learning methods to predict drug concentration in plasma and describe the...

A CPG-Based Versatile Control Framework for Metameric Earthworm-Like Robotic Locomotion.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Annelids such as earthworms are considered to have central pattern generators (CPGs) that generate rhythms in neural circuits to coordinate the deformation of body segments for effective locomotion. At present, the states of earthworm-like robot segm...

Exploring the expressiveness of abstract metabolic networks.

PloS one
Metabolism is characterised by chemical reactions linked to each other, creating a complex network structure. The whole metabolic network is divided into pathways of chemical reactions, such that every pathway is a metabolic function. A simplified re...

Artificial Intelligence and Machine Learning Approaches to Facilitate Therapeutic Drug Management and Model-Informed Precision Dosing.

Therapeutic drug monitoring
BACKGROUND: Therapeutic drug monitoring (TDM) and model-informed precision dosing (MIPD) have greatly benefitted from computational and mathematical advances over the past 60 years. Furthermore, the use of artificial intelligence (AI) and machine lea...

High precision tracking analysis of cell position and motion fields using 3D U-net network models.

Computers in biology and medicine
Cells are the basic units of biological organization, and the quantitative analysis of cellular states is an important topic in medicine and is valuable in revealing the complex mechanisms of microscopic world organisms. In order to better understand...

Machine Learning for Pharmacokinetic/Pharmacodynamic Modeling.

Journal of pharmaceutical sciences
A variety of new recurrent neural networks (RNNs) including the ODE-LSTM, Phased LSTM, CTGRU and GRU-D, were evaluated on modeling irregularly sampled PK/PD data with 6 or 12 time points/day and predicting PD data of unseen dosing regimens and dosing...

An at-scale tailless flapping wing hummingbird robot: II. Flight control in hovering and trajectory tracking.

Bioinspiration & biomimetics
Flight control such as stable hovering and trajectory tracking of tailless flapping-wing micro aerial vehicles is a challenging task. Given the constraint on actuation capability, flight control authority is limited beyond sufficient lift generation....

Computational Predictions of Nonclinical Pharmacokinetics at the Drug Design Stage.

Journal of chemical information and modeling
Although computational predictions of pharmacokinetics (PK) are desirable at the drug design stage, existing approaches are often limited by prediction accuracy and human interpretability. Using a discovery data set of mouse and rat PK studies at Roc...