AIMC Topic: Models, Biological

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Evolution of hospitalized patient characteristics through the first three COVID-19 waves in Paris area using machine learning analysis.

PloS one
Characteristics of patients at risk of developing severe forms of COVID-19 disease have been widely described, but very few studies describe their evolution through the following waves. Data was collected retrospectively from a prospectively maintain...

Machine learning methods to predict presence of residual cancer following hysterectomy.

Scientific reports
Surgical management for gynecologic malignancies often involves hysterectomy, often constituting the most common gynecologic surgery worldwide. Despite maximal surgical and medical care, gynecologic malignancies have a high rate of recurrence followi...

Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine.

Scientific reports
Temporal dataset shift associated with changes in healthcare over time is a barrier to deploying machine learning-based clinical decision support systems. Algorithms that learn robust models by estimating invariant properties across time periods for ...

Exponential Stability of Mixed Time-Delay Neural Networks Based on Switching Approaches.

IEEE transactions on cybernetics
Neural networks (NNs) have been deeply studied due to their wide applicability. Since time delays are unavoidable in reality, it is basic and crucial for all applications based on NNs to guarantee system stability under the influence of mixed time de...

Machine Learning Predicts Biogeochemistry from Microbial Community Structure in a Complex Model System.

Microbiology spectrum
Microbial community structure is influenced by the environment and in turn exerts control on many environmental parameters. We applied this concept in a bioreactor study to test whether microbial community structure contains information sufficient to...

Toward the biological model of the hippocampus as the successor representation agent.

Bio Systems
The hippocampus is an essential brain region for spatial memory and learning. Recently, a theoretical model of the hippocampus based on temporal difference (TD) learning has been published. Inspired by the successor representation (SR) learning algor...

Positional SHAP (PoSHAP) for Interpretation of machine learning models trained from biological sequences.

PLoS computational biology
Machine learning with multi-layered artificial neural networks, also known as "deep learning," is effective for making biological predictions. However, model interpretation is challenging, especially for sequential input data used with recurrent neur...

A hybrid neural network for driving behavior risk prediction based on distracted driving behavior data.

PloS one
Distracted driving behavior is one of the main factors of road accidents. Accurately predicting the risk of driving behavior is of great significance to the active safety of road transportation. The large amount of information collected by the sensor...

Development and Validation of Clinical Diagnostic Model for Girls with Central Precocious Puberty: Machine-learning Approaches.

PloS one
BACKGROUND: A brief gonadotropin-releasing hormone analogues (GnRHa) stimulation test which solely focused on LH 30-minute post-stimulation was considered to identify girls with central precocious puberty (CPP). However, it was tested using tradition...

Automated annotation of birdsong with a neural network that segments spectrograms.

eLife
Songbirds provide a powerful model system for studying sensory-motor learning. However, many analyses of birdsong require time-consuming, manual annotation of its elements, called syllables. Automated methods for annotation have been proposed, but th...