AIMC Topic: Computer Simulation

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High-dimensional multiple imputation for partially observed confounders including natural language processing-derived auxiliary covariates.

American journal of epidemiology
Multiple imputation (MI) models can be improved with auxiliary covariates (ACs), but their performance in high-dimensional data remains unclear. We aimed to develop and compare high-dimensional MI (HDMI) methods using structured and natural language ...

[Localizing target for transcranial electrical stimulation in epilepsy patients combining scalp electroencephalogram and neural computational model].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
For patients with MRI-negative drug-resistant epilepsy, noninvasive localization of targets for transcranial electrical stimulation (tES) remains a clinical challenge. This study proposes a novel target localization approach that integrates electroen...

Working Memory and Self-Directed Inner Speech Enhance Multitask Generalization in Active Inference.

Neural computation
This simulation study shows how a set of working memory tasks can be acquired simultaneously through interaction between a stacked recurrent neural network (RNN) and multiple working memories. In these tasks, temporal patterns are provided, followed ...

Speaking Mathematical Models into Existence.

Cancer research
Mathematical and computational modeling enables in silico testing of hypotheses, experimental design, and interventional strategies. However, building, sharing, and applying complex models require technical skills and software development knowledge t...

"MR Fingerprinting for Imaging Brain Hemodynamics and Oxygenation".

Journal of magnetic resonance imaging : JMRI
Over the past decade, several studies have explored the potential of magnetic resonance fingerprinting (MRF) for the quantification of brain hemodynamics, oxygenation, and perfusion. Recent advances in simulation models and reconstruction frameworks ...

Assessing subvisible particle risks in monoclonal antibodies: insights from quartz crystal microbalance with dissipation, machine learning, and in silico analysis.

mAbs
Throughout the lifecycle of biopharmaceutical development and manufacturing, monoclonal antibodies (mAbs) are subjected to diverse interfacial stresses and encounter various container surfaces. These interactions can cause the formation of subvisible...

PROPERMAB: an integrative framework for prediction of antibody developability using machine learning.

mAbs
Selection of lead therapeutic molecules is often driven predominantly by pharmacological efficacy and safety. Candidate developability, such as biophysical properties that affect the formulation of the molecule into a product, is usually evaluated on...

In Silico Digital Twins of Bone Metastasis Enable Investigation of Tumor Progression and Therapy Response.

Cancer research
UNLABELLED: Bone metastasis (BM) is a leading cause of morbidity and mortality in patients with prostate and renal cancer. The complex and dynamic biological processes driving its progression present significant challenges for both understanding and ...

A meta-learning method for estimation of causal excursion effects to assess time-varying moderation.

Biometrics
Advances in wearable technologies and health interventions delivered by smartphones have greatly increased the accessibility of mobile health (mHealth) interventions. Micro-randomized trials (MRTs) are designed to assess the effectiveness of the mHea...

Antioxidant bioactivity of sunflower protein hydrolysates in Caco-2 cells and in silico structural properties.

Food chemistry
Sunflower protein hydrolysate (SPH), with 95 % reduced phenolic content, was studied for its protective effects against oxidative stress in intestinal cells (Caco-2). Produced via alcalase hydrolysis, SPH's molecular weight, amino acid composition, a...