AI Medical Compendium Topic

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Models, Biological

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A Machine Learning Algorithm to Predict the Starting Dose of Daptomycin.

Clinical pharmacokinetics
BACKGROUND AND OBJECTIVE: The dosage of daptomycin is usually based on body weight. However, it has been shown that this approach yields too high an exposure in obese patients. Pharmacokinetic and pharmacodynamic indexes (PK/PD) have been proposed fo...

Using deep learning for predicting the dynamic evolution of breast cancer migration.

Computers in biology and medicine
BACKGROUND: Breast cancer (BC) remains a prevalent health concern, with metastasis as the main driver of mortality. A detailed understanding of metastatic processes, particularly cell migration, is fundamental to improve therapeutic strategies. The w...

Quantifying massively parallel microbial growth with spatially mediated interactions.

PLoS computational biology
Quantitative understanding of microbial growth is an essential prerequisite for successful control of pathogens as well as various biotechnology applications. Even though the growth of cell populations has been extensively studied, microbial growth r...

Cell factory design with advanced metabolic modelling empowered by artificial intelligence.

Metabolic engineering
Advances in synthetic biology and artificial intelligence (AI) have provided new opportunities for modern biotechnology. High-performance cell factories, the backbone of industrial biotechnology, are ultimately responsible for determining whether a b...

Gtie-Rt: A comprehensive graph learning model for predicting drugs targeting metabolic pathways in human.

Journal of bioinformatics and computational biology
Drugs often target specific metabolic pathways to produce a therapeutic effect. However, these pathways are complex and interconnected, making it challenging to predict a drug's potential effects on an organism's overall metabolism. The mapping of dr...

Achieving Occam's razor: Deep learning for optimal model reduction.

PLoS computational biology
All fields of science depend on mathematical models. Occam's razor refers to the principle that good models should exclude parameters beyond those minimally required to describe the systems they represent. This is because redundancy can lead to incor...

Leading-edge curvature effect on aerodynamic performance of flapping wings in hover and forward flight.

Bioinspiration & biomimetics
This study investigates the role of leading-edge (LE) curvature in flapping wing aerodynamics considering hovering and forward flight conditions. A scaled-up robotic model is towed along its longitudinal axis by a rack gear carriage system. The forwa...

Machine Learning Approach in Dosage Individualization of Isoniazid for Tuberculosis.

Clinical pharmacokinetics
INTRODUCTION: Isoniazid is a first-line antituberculosis agent with high variability, which would profit from individualized dosing. Concentrations of isoniazid at 2 h (C), as an indicator of safety and efficacy, are important for optimizing therapy.

On the analysis and control of a bipedal legged locomotion model via partial feedback linearization.

Bioinspiration & biomimetics
In this study, we introduce a new model for bipedal locomotion that enhances the classical spring-loaded inverted pendulum (SLIP) model. Our proposed model incorporates a damping term in the leg spring, a linear actuator serially interconnected to th...

Multi-Task ADME/PK prediction at industrial scale: leveraging large and diverse experimental datasets.

Molecular informatics
ADME (Absorption, Distribution, Metabolism, Excretion) properties are key parameters to judge whether a drug candidate exhibits a desired pharmacokinetic (PK) profile. In this study, we tested multi-task machine learning (ML) models to predict ADME a...