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Entropy

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Reliable CA-(Q)SAR generation based on entropy weight optimized by grid search and correction factors.

Computers in biology and medicine
Chromosome aberration (CA) is a serious genotoxicity of a compound, leading to carcinogenicity and developmental side effects. In the present manuscript, we developed a QSAR model for CA prediction using artificial intelligence methodologies. The rel...

Packaging Big Data Visualization Based on Computational Intelligence Information Design.

Computational intelligence and neuroscience
A method based on a computational intelligence information model is proposed to study the visualization of large data packages. Since the CAIM algorithm only considers the distribution of the largest number of classes in an interval, it offers an opt...

Accurate Prediction of Aqueous Free Solvation Energies Using 3D Atomic Feature-Based Graph Neural Network with Transfer Learning.

Journal of chemical information and modeling
Graph neural network (GNN)-based deep learning (DL) models have been widely implemented to predict the experimental aqueous solvation free energy, while its prediction accuracy has reached a plateau partly due to the scarcity of available experimenta...

Emotion Recognition from Physiological Channels Using Graph Neural Network.

Sensors (Basel, Switzerland)
In recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presente...

Semi-Supervised Learning for Defect Segmentation with Autoencoder Auxiliary Module.

Sensors (Basel, Switzerland)
In general, one may have access to a handful of labeled normal and defect datasets. Most unlabeled datasets contain normal samples because the defect samples occurred rarely. Thus, the majority of approaches for anomaly detection are formed as unsupe...

Improving Predictions with a Multitask Convolutional Siamese Network.

Journal of chemical information and modeling
The lead optimization phase of drug discovery refines an initial hit molecule for desired properties, especially potency. Synthesis and experimental testing of the small perturbations during this refinement can be quite costly and time-consuming. Rel...

Multitask Machine Learning of Collective Variables for Enhanced Sampling of Rare Events.

Journal of chemical theory and computation
Computing accurate reaction rates is a central challenge in computational chemistry and biology because of the high cost of free energy estimation with unbiased molecular dynamics. In this work, a data-driven machine learning algorithm is devised to ...

Contingency response decision of network public opinion emergencies based on intuitionistic fuzzy entropy and preference information of decision makers.

Scientific reports
A multi-attribute group decision-making (MAGDM) method based on intuitionistic fuzzy preference information is proposed for the multi-attribute intuitionistic fuzzy group decision-making problem where the decision-makers weight and attribute weight a...

Extended DeepILST for Various Thermodynamic States and Applications in Coarse-Graining.

The journal of physical chemistry. A
Molecular dynamics (MD) simulations are widely used to obtain the microscopic properties of atomistic systems when the interatomic potential or the coarse-grained potential is known. In many practical situations, however, it is necessary to predict t...

GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling.

Journal of chemical theory and computation
We introduce a Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and free energy profiling workflow (GLOW) to predict molecular determinants and map free energy landscapes of biomolecules. All-atom GaMD-enhanced sampling simulations...