AIMC Topic: Computer Simulation

Clear Filters Showing 241 to 250 of 4054 articles

Validation of OncoOrigin: An Integrative AI Tool for Primary Cancer Site Prediction with Graphical User Interface to Facilitate Clinical Application.

International journal of molecular sciences
Cancers of unknown primary (CUPs) represent a significant diagnostic and therapeutic challenge in the field of oncology. Due to the limitations of current diagnostic tools in these cases, novel approaches must be brought forward to improve treatment ...

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...

Development of hybrid robust model based on computational modeling and machine learning for analysis of drug sorption onto porous adsorbents.

Scientific reports
This study investigates the utilization of three regression models, i.e., Kernel Ridge Regression (KRR), nu-Support Vector Regression ([Formula: see text]-SVR), and Polynomial Regression (PR) for the purpose of forecasting the concentration (C) of a ...

A fuzzy robust optimization model for dual objective forward and reverse logistics networks considering carbon emissions.

PloS one
The inherent unpredictability within the low-carbon integrated supply chain logistics network complicates its management. This paper endeavours to address the challenge of designing a low-carbon logistics network within a context of uncertainty and w...

Physics-informed machine learning for automatic model reduction in chemical reaction networks.

Scientific reports
Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. In chemical reaction network modeling, this synergy proves valuable, addressing the high computati...

Deep reinforcement learning for multi-targets propofol dosing.

Journal of clinical monitoring and computing
The administration of propofol for sedation or general anesthesia presents challenges due to the complex relationship between patient factors and real-time physiological responses. This study explores the application of deep reinforcement learning (D...

Mechanical Structure Design and Motion Simulation Analysis of a Lower Limb Exoskeleton Rehabilitation Robot Based on Human-Machine Integration.

Sensors (Basel, Switzerland)
Population aging is an inevitable trend in contemporary society, and the application of technologies such as human-machine interaction, assistive healthcare, and robotics in daily service sectors continues to increase. The lower limb exoskeleton reha...

Using deep reinforcement learning to investigate stretch feedback during swimming of the lamprey.

Bioinspiration & biomimetics
Animals have to navigate complex environments and perform intricate swimming maneuvers in the real world. To conquer these challenges, animals evolved a variety of motion control strategies. While it is known that many factors contribute to motion co...

Modeling crash avoidance behaviors in vehicle-pedestrian near-miss scenarios: Curvilinear time-to-collision and Mamba-driven deep reinforcement learning.

Accident; analysis and prevention
Interactions between vehicle-pedestrian at intersections often lead to safety-critical situations. This study aims to model the crash avoidance behaviors of vehicles during interactions with pedestrians in near-miss scenarios, contributing to the dev...

Enhancing Blood-Brain Barrier Penetration Prediction by Machine Learning-Based Integration of Novel and Existing, In Silico and Experimental Molecular Parameters from a Standardized Database.

Journal of chemical information and modeling
Predicting blood-brain barrier (BBB) penetration is crucial for developing central nervous system (CNS) drugs, representing a significant hurdle in successful clinical phase I studies. One of the most valuable properties for this prediction is the po...