AIMC Topic: Models, Biological

Clear Filters Showing 251 to 260 of 1371 articles

Application of machine learning techniques in population pharmacokinetics/pharmacodynamics modeling.

Drug metabolism and pharmacokinetics
Population pharmacokinetics/pharmacodynamics (pop-PK/PD) consolidates pharmacokinetic and pharmacodynamic data from many subjects to understand inter- and intra-individual variability due to patient backgrounds, including disease state and genetics. ...

Exploring Transformer Model in Longitudinal Pharmacokinetic/Pharmacodynamic Analyses and Comparing with Alternative Natural Language Processing Models.

Journal of pharmaceutical sciences
There remains a substantial need for a comprehensive assessment of various natural language processing (NLP) algorithms in longitudinal pharmacokinetic/pharmacodynamic (PK/PD) modeling despite recent advances in machine learning in the space of quant...

Enhancement of aerodynamic performance of a bristled wing by elliptic cylinders.

Bioinspiration & biomimetics
Enhancing the aerodynamic performance of bristled wings is an important topic for small flying robotics. This paper numerically investigates this situation at very low Reynolds numbers by using elliptic cylinders as the bristles instead of circular c...

A neural network model for the evolution of learning in changing environments.

PLoS computational biology
Learning from past experience is an important adaptation and theoretical models may help to understand its evolution. Many of the existing models study simple phenotypes and do not consider the mechanisms underlying learning while the more complex ne...

Machine learning interpretable models of cell mechanics from protein images.

Cell
Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. Currently, no systematic strategy exists to infer large-scale physical properties of a cell from its molecular components. This is an obstacle to understandi...

A computational tumor growth model experience based on molecular dynamics point of view using deep cellular automata.

Artificial intelligence in medicine
Cancer, as identified by the World Health Organization, stands as the second leading cause of death globally. Its intricate nature makes it challenging to study solely based on biological knowledge, often leading to expensive research endeavors. Whil...

Learning and Reusing Quadruped Robot Movement Skills from Biological Dogs for Higher-Level Tasks.

Sensors (Basel, Switzerland)
In the field of quadruped robots, the most classic motion control algorithm is based on model prediction control (MPC). However, this method poses challenges as it necessitates the precise construction of the robot's dynamics model, making it difficu...

Mechanism-aware and multimodal AI: beyond model-agnostic interpretation.

Trends in cell biology
Artificial intelligence (AI) is widely used for exploiting multimodal biomedical data, with increasingly accurate predictions and model-agnostic interpretations, which are however also agnostic to biological mechanisms. Combining metabolic modelling,...

Improving on in-silico prediction of oral drug bioavailability.

Expert opinion on drug metabolism & toxicology
INTRODUCTION: Although significant development has been made in high-throughput screening of oral drug absorption and oral bioavailability, prediction continues to play an important role in prediction of oral bioavailability and assisting in the pro...

Reliable interpretability of biology-inspired deep neural networks.

NPJ systems biology and applications
Deep neural networks display impressive performance but suffer from limited interpretability. Biology-inspired deep learning, where the architecture of the computational graph is based on biological knowledge, enables unique interpretability where re...