AIMC Topic: Computer Simulation

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Center-surround inhibition in expectation and its underlying computational and artificial neural network models.

eLife
Expectation is beneficial for adaptive behavior through quickly deducing plausible interpretations of information. The profile and underlying neural computations of this process, however, remain unclear. When participants expected a grating with a sp...

Meltome Atlas of Arabidopsis thaliana proteome: a melting temperature-based identification of heat and cold resistant proteins using in-silico approach.

BMC genomics
BACKGROUND: Plants are always exposed to a variety of stressful environments, including heat and drought stress, which severely impact the growth, development, and productivity of the plants. To overcome such challenges, plants have evolved diverse a...

Identification of novel biomarkers for epithelial ovarian cancer through machine learning and explainable artificial intelligence using in silico and in vitro analysis.

Scientific reports
Epithelial ovarian cancer (EOC) is a lethal gynecological malignancy. Ongoing research aimed to identify novel biomarkers and develop combined algorithms to improve diagnosis and prognosis prediction for EOC. RNA-seq related to EOC were obtained from...

Dynamics and energetics of dual-spring force couples in torque reversal systems.

Bioinspiration & biomimetics
Latch-mediated spring actuation systems leverage the interplay of springs and latches to rapidly accelerate a load. In biological systems, elastic energy is often distributed across multiple structures, resulting in forces applied from multiple sprin...

Quantifying the speed-accuracy trade-off of large language models on oral and maxillofacial surgery multiple-choice questions.

Scientific reports
Large language models (LLMs) such as GPT-4o, Copilot and Gemini are entering dental curricula, yet their suitability for real-time decision support remains unclear because most evaluations report accuracy alone. This prospective in silico diagnostic-...

Meta simulation approach for evaluating machine learning method selection in data limited settings.

Scientific reports
Selecting appropriate machine learning (ML) methods for domain-specific tasks remains a persistent challenge, particularly in medicine where datasets are often small, heterogeneous, and incomplete. Traditional benchmarking strategies rely on limited ...

Opportunities for AI-based Model-informed Drug Development: A Comparative Analysis of NONMEM and AI-based Models for Population Pharmacokinetic Prediction.

The AAPS journal
Model-informed drug development (MIDD) plays an important role in pharmacometrics by leveraging mathematical models to optimize drug dosing strategies. Traditional methods such as nonlinear mixed effects modeling (NONMEM) have long been the gold stan...

Toward in-silico data assessment for passive BCIs: generating EEG rhythms with GANs.

Journal of neural engineering
Passive brain-computer interface (BCI) based on electroencephalography (EEG) has gained traction as reliable method for monitoring human vigilance in attention-demanding critical contexts. Unfortunately, the lack of extensive public datasets compromi...

Path planning of locust-inspired jumping robots in obstacle-dense environments using curriculum reinforcement learning.

Bioinspiration & biomimetics
Biologically-inspired jumping robots have demonstrated remarkable adaptability in complex environments, making them increasingly valuable across various fields. However, effective path planning in obstacle-dense environments for large-scale jumping r...

Mobot mobot: an ocean sunfish () robot.

Bioinspiration & biomimetics
The Ocean Sunfish () has one of the most unusual body geometries and swimming strategies of all fish species. Effectively lacking a caudal fin, these fish propel themselves by synchronized flapping of their extremely long dorsal and anal fins-a form ...