AIMC Topic: Machine Learning

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An introduction to machine learning tools for the analysis of microplastics in complex matrices.

Environmental science. Processes & impacts
As microplastic (MP) particles continue to spread globally, their pervasive presence is increasingly problematic. Analyzing MPs in matrices as varied as soil, river water, and biosolid fertilizers is critical, as these matrices directly impact the fo...

Can artificial intelligence lower the global sudden cardiac death rate? A narrative review.

Journal of electrocardiology
PURPOSE OF REVIEW: WHO defines SCD as sudden unexpected death either within 1 h of symptom onset (witnessed) or within 24 h of having been observed alive and symptom-free (unwitnessed). Sudden cardiac arrest is a major cause of mortality worldwide, w...

Prediction Trough Concentrations of Valproic Acid Among Chinese Adult Patients with Epilepsy Using Machine Learning Techniques.

Pharmaceutical research
OBJECTIVE: This study aimed to establish an optimal model based on machine learning (ML) to predict Valproic acid (VPA) trough concentrations in Chinese adult epilepsy patients.

Identifying Neuro-Inflammatory Biomarkers of Generalized Anxiety Disorder from Lymphocyte Subsets Based on Machine Learning Approaches.

Neuropsychobiology
INTRODUCTION: Activation of the inflammatory response system is involved in the pathogenesis of generalized anxiety disorder (GAD). The purpose of this study was to identify and characterize inflammatory biomarkers in the diagnosis of GAD based on ma...

Autonomous learning of generative models with chemical reaction network ensembles.

Journal of the Royal Society, Interface
Can a micron-sized sack of interacting molecules autonomously learn an internal model of a complex and fluctuating environment? We draw insights from control theory, machine learning theory, chemical reaction network theory and statistical physics to...

Dual inhibition of AChE and MAO-B in Alzheimer's disease: machine learning approaches and model interpretations.

Molecular diversity
Alzheimer's disease (AD) is one of the most prevalent neurodegenerative diseases. Given the multifactorial pathophysiology of AD, monotargeted agents can only alleviate symptoms but not cure AD. Acetylcholinesterase (AChE) and Monoamine oxidase B (MA...

A rule- and query-guided reinforcement learning for extrapolation reasoning in temporal knowledge graphs.

Neural networks : the official journal of the International Neural Network Society
Extrapolation reasoning in temporal knowledge graphs (TKGs) aims at predicting future facts based on historical data, and finds extensive application in diverse real-world scenarios. Existing TKG reasoning methods primarily focus on capturing the fac...

Continual learning with Bayesian compression for shared and private latent representations.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a new continual learning method with Bayesian Compression for Shared and Private Latent Representations (BCSPLR), which learns a compact model structure while preserving the accuracy. In Shared and Private Latent Representations (...

Tensor neural networks for high-dimensional Fokker-Planck equations.

Neural networks : the official journal of the International Neural Network Society
We solve high-dimensional steady-state Fokker-Planck equations on the whole space by applying tensor neural networks. The tensor networks are a linear combination of tensor products of one-dimensional feedforward networks or a linear combination of s...

Multi-view learning with enhanced multi-weight vector projection support vector machine.

Neural networks : the official journal of the International Neural Network Society
Multi-view learning aims on learning from the data represented by multiple distinct feature sets. Various multi-view support vector machine methods have been successfully applied to classification tasks. However, the existed methods often face the pr...