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Influenza Vaccines

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Comparative Study on the Efficacy of MF 59, ISA70 VG, and Nano-Aluminum Hydroxide Adjuvants, Alone and with Nano-Selenium on Humoral Immunity Induced by a Bivalent Newcastle+Avian Influenza Vaccine in Chickens.

Archives of Razi Institute
Newcastle disease (ND) and Avian influenza (AI) are the major problems and the most economically important viral diseases in the poultry industry; therefore, vaccination against these diseases is considered one of the most effective ways of preventio...

Time series computational prediction of vaccines for influenza A H3N2 with recurrent neural networks.

Journal of bioinformatics and computational biology
Influenza viruses are persistently threatening public health, causing annual epidemics and sporadic pandemics due to rapid viral evolution. Vaccines are used to prevent influenza infections but the composition of the influenza vaccines have to be upd...

Machine learning models to identify low adherence to influenza vaccination among Korean adults with cardiovascular disease.

BMC cardiovascular disorders
BACKGROUND: Annual influenza vaccination is an important public health measure to prevent influenza infections and is strongly recommended for cardiovascular disease (CVD) patients, especially in the current coronavirus disease 2019 (COVID-19) pandem...

The risk of racial bias while tracking influenza-related content on social media using machine learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Machine learning is used to understand and track influenza-related content on social media. Because these systems are used at scale, they have the potential to adversely impact the people they are built to help. In this study, we explore t...

Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Automated analysis of vaccine postmarketing surveillance narrative reports is important to understand the progression of rare but severe vaccine adverse events (AEs). This study implemented and evaluated state-of-the-art deep learning algo...

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...

Identification of gene and protein signatures associated with long-term effects of COVID-19 on the immune system after patient recovery by analyzing single-cell multi-omics data using a machine learning approach.

Vaccine
Viral infections significantly impact the immune system, and impact will persist until recovery. However, the influence of severe acute respiratory syndrome coronavirus 2 infection on the homeostatic immune status and secondary immune response in rec...

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...

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...