The electrohysterogram (EHG) is a promising means of monitoring pregnancy and of detecting a risk of preterm labor. To improve our understanding of the EHG as well as its relationship with the physiologic phenomena involved in uterine contractility, we plan to model these phenomena in terms of generation and propagation of uterine electrical activity. This activity can be realistically modeled by representing the principal ionic dynamics at the cell level, the propagation of electrical activity at the tissue level and then the way it is reflected on the skin surface through the intervening tissue. We present in this paper the different steps leading to the development and validation of a biophysics based multiscale model of the EHG, going from the cell to the electrical signal measured on the abdomen.

Download full-text PDF

Source
http://dx.doi.org/10.1109/EMBC.2013.6611280DOI Listing

Publication Analysis

Top Keywords

multiscale model
8
electrical activity
8
model electrohysterogram
4
electrohysterogram biomodue_ptl
4
biomodue_ptl project
4
project electrohysterogram
4
electrohysterogram ehg
4
ehg promising
4
promising monitoring
4
monitoring pregnancy
4

Similar Publications

AI-driven multi-omics integration for multi-scale predictive modeling of genotype-environment-phenotype relationships.

Comput Struct Biotechnol J

January 2025

Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, NY, USA.

Despite the wealth of single-cell multi-omics data, it remains challenging to predict the consequences of novel genetic and chemical perturbations in the human body. It requires knowledge of molecular interactions at all biological levels, encompassing disease models and humans. Current machine learning methods primarily establish statistical correlations between genotypes and phenotypes but struggle to identify physiologically significant causal factors, limiting their predictive power.

View Article and Find Full Text PDF

Crystalline pentacene is a model solid-state light-harvesting material because its quantum efficiencies exceed 100% via ultrafast singlet fission. The singlet fission mechanism in pentacene crystals is disputed due to insufficient electronic information in time-resolved experiments and intractable quantum mechanical calculations for simulating realistic crystal dynamics. Here we combine a multiscale multiconfigurational approach and machine learning photodynamics to understand competing singlet fission mechanisms in crystalline pentacene.

View Article and Find Full Text PDF

Understanding the mechanics linking cortical folding and brain connectivity is crucial for both healthy and abnormal brain development. Despite the importance of this relationship, existing models fail to explain how growing axon bundles navigate the stress field within a folding brain or how this bidirectional and dynamic interaction shapes the resulting surface morphologies and connectivity patterns. Here, we propose the concept of "axon reorientation" and formulate a mechanical model to uncover the dynamic multiscale mechanics of the linkages between cortical folding and connectivity development.

View Article and Find Full Text PDF

Traumatic brain injuries present significant diagnostic challenges in emergency medicine, where the timely interpretation of medical images is crucial for patient outcomes. In this paper, we propose a novel AI-based approach for automatic radiology report generation tailored to cranial trauma cases. Our model integrates an AC-BiFPN with a Transformer architecture to capture and process complex medical imaging data such as CT and MRI scans.

View Article and Find Full Text PDF

A novel ANN-based feature subset selection in multi-scale granular ball neighborhood decision tables.

Neural Netw

January 2025

School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, Fujian 363000, China. Electronic address:

As an effective data preprocessing method, feature subset selection has been widely explored in recent years. However, the feature subset selection for the Wu-Leung model and its extended model involves high time complexity. Therefore, we combine the granular ball neighborhood rough set with the Wu-Leung model.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!