AIMC Topic: Models, Biological

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Performance evaluation in [18F]Florbetaben brain PET images classification using 3D Convolutional Neural Network.

PloS one
High accuracy has been reported in deep learning classification for amyloid brain scans, an important factor in Alzheimer's disease diagnosis. However, the possibility of overfitting should be considered, as this model is fitted with sample data. The...

Deep learning allows genome-scale prediction of Michaelis constants from structural features.

PLoS biology
The Michaelis constant KM describes the affinity of an enzyme for a specific substrate and is a central parameter in studies of enzyme kinetics and cellular physiology. As measurements of KM are often difficult and time-consuming, experimental estima...

Simulation and Prediction of Fungal Community Evolution Based on RBF Neural Network.

Computational and mathematical methods in medicine
Simulation and prediction of the scale change of fungal community. First, using the experimental data of a variety of fungal decomposition activities, a mathematical model of the decomposition rate and the relationship between the bacterial species w...

The simulation experiment description markup language (SED-ML): language specification for level 1 version 4.

Journal of integrative bioinformatics
Computational simulation experiments increasingly inform modern biological research, and bring with them the need to provide ways to annotate, archive, share and reproduce the experiments performed. These simulations increasingly require extensive co...

Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data.

Nature plants
Four species of grass generate half of all human-consumed calories. However, abundant biological data on species that produce our food remain largely inaccessible, imposing direct barriers to understanding crop yield and fitness traits. Here, we asse...

Competency of Neural Networks for the Numerical Treatment of Nonlinear Host-Vector-Predator Model.

Computational and mathematical methods in medicine
The aim of this work is to introduce a stochastic solver based on the Levenberg-Marquardt backpropagation neural networks (LMBNNs) for the nonlinear host-vector-predator model. The nonlinear host-vector-predator model is dependent upon five classes, ...

eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19.

PloS one
We present an interpretable machine learning algorithm called 'eARDS' for predicting ARDS in an ICU population comprising COVID-19 patients, up to 12-hours before satisfying the Berlin clinical criteria. The analysis was conducted on data collected f...

Multi-step validation of a deep learning-based system for the quantification of bowel preparation: a prospective, observational study.

The Lancet. Digital health
BACKGROUND: Inadequate bowel preparation is associated with a decrease in adenoma detection rate (ADR). A deep learning-based bowel preparation assessment system based on the Boston bowel preparation scale (BBPS) has been previously established to ca...

Personalised Medicine for Colorectal Cancer Using Mechanism-Based Machine Learning Models.

International journal of molecular sciences
Gaining insight into the mechanisms of signal transduction networks (STNs) by using critical features from patient-specific mathematical models can improve patient stratification and help to identify potential drug targets. To achieve this, these mod...