AIMC Topic: Influenza A Virus, H1N1 Subtype

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Enhancing explainability in epidemiological predictions using fuzzy logic integrated with machine and deep learning algorithms.

Scientific reports
Epidemiological data is often analyzed without fully accounting for the uncertainties that are key to understanding the nuances of the dataset. While traditional approaches like the SIR mathematical model provide valuable insights, our study aims to ...

Machine learning-assisted affinity ultrafiltration for bioactive natural products discovery:Application to screening of neuraminidase inhibitors from medicinal herbs.

Analytica chimica acta
BACKGROUND: Bioactive natural products represent a vital resource for combating human diseases. However, their discovery often encounters multiple challenges. Bioactivity-guided isolation can yield bioactive compounds but are labor-intensive and have...

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...

Combining Digital and Molecular Approaches Using Health and Alternate Data Sources in a Next-Generation Surveillance System for Anticipating Outbreaks of Pandemic Potential.

JMIR public health and surveillance
Globally, millions of lives are impacted every year by infectious diseases outbreaks. Comprehensive and innovative surveillance strategies aiming at early alert and timely containment of emerging and reemerging pathogens are a pressing priority. Shor...

DeepFlu: a deep learning approach for forecasting symptomatic influenza A infection based on pre-exposure gene expression.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Not everyone gets sick after an exposure to influenza A viruses (IAV). Although KLRD1 has been identified as a potential biomarker for influenza susceptibility, it remains unclear whether forecasting symptomatic flu infectio...

Convolutional Neural Network Based Approach to in Silico Non-Anticipating Prediction of Antigenic Distance for Influenza Virus.

Viruses
Evaluation of the antigenic similarity degree between the strains of the influenza virus is highly important for vaccine production. The conventional method used to measure such a degree is related to performing the immunological assays of hemaggluti...

Anti-pandemic influenza A (H1N1) virus potential of catechin and gallic acid.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: The pandemic influenza A (H1N1) virus has spread worldwide and infected a large proportion of the human population. Discovery of new and effective drugs for the treatment of influenza is a crucial issue for the global medical community. A...