AIMC Topic: Influenza, Human

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Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation.

International journal of molecular sciences
Transient receptor potential vanilloid 4 (TRPV4) is a calcium-permeable cation channel critical for maintaining intracellular Ca homeostasis and is essential in regulating immune responses, metabolic processes, and signal transduction. Recent studies...

Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak.

Artificial intelligence in medicine
BACKGROUND: Controlling re-emerging outbreaks such as COVID-19 is a critical concern to global health. Disease forecasting solutions are extremely beneficial to public health emergency management. This work aims to design and deploy a framework for r...

A novel graph neural network based approach for influenza-like illness nowcasting: exploring the interplay of temporal, geographical, and functional spatial features.

BMC public health
BACKGROUND: Accurate and timely monitoring of influenza prevalence is essential for effective healthcare interventions. This study proposes a graph neural network (GNN)-based method to address the issue of cross-regional connectivity in predicting in...

Artificial intelligence in respiratory pandemics-ready for disease X? A scoping review.

European radiology
OBJECTIVES: This study aims to identify repeated previous shortcomings in medical imaging data collection, curation, and AI-based analysis during the early phase of respiratory pandemics. Based on the results, it seeks to highlight essential steps fo...

FluPMT: Prediction of Predominant Strains of Influenza A Viruses via Multi-Task Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Seasonal influenza vaccines play a crucial role in saving numerous lives annually. However, the constant evolution of the influenza A virus necessitates frequent vaccine updates to ensure its ongoing effectiveness. The decision to develop a new vacci...

Development, study, and comparison of models of cross-immunity to the influenza virus using statistical methods and machine learning.

Voprosy virusologii
INTRODUCTION: The World Health Organization considers the values of antibody titers in the hemagglutination inhibition assay as one of the most important criteria for assessing successful vaccination. Mathematical modeling of cross-immunity allows fo...

Integrated epigenomic exposure signature discovery.

Epigenomics
The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Here we developed and implemented a machine learning algorithm, the exposure signature discove...

Estimating epidemic trajectories of SARS-CoV-2 and influenza A virus based on wastewater monitoring and a novel machine learning algorithm.

The Science of the total environment
The COVID-19 pandemic has altered the circulation of non-SARS-CoV-2 respiratory viruses. In this study, we carried out wastewater surveillance of SARS-CoV-2 and influenza A virus (IAV) in three key port cities in China through real-time quantitative ...

Forecasting and analyzing influenza activity in Hebei Province, China, using a CNN-LSTM hybrid model.

BMC public health
BACKGROUND: Influenza, an acute infectious respiratory disease, presents a significant global health challenge. Accurate prediction of influenza activity is crucial for reducing its impact. Therefore, this study seeks to develop a hybrid Convolution ...

Seasonal antigenic prediction of influenza A H3N2 using machine learning.

Nature communications
Antigenic characterization of circulating influenza A virus (IAV) isolates is routinely assessed by using the hemagglutination inhibition (HI) assays for surveillance purposes. It is also used to determine the need for annual influenza vaccine update...