A survey on multi-task learning
Multi-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to
leverage useful information contained in multiple related tasks to help improve the …
leverage useful information contained in multiple related tasks to help improve the …
[HTML][HTML] Antigenic characterization of influenza and SARS-CoV-2 viruses
Antigenic characterization of emerging and re-emerging viruses is necessary for the
prevention of and response to outbreaks, evaluation of infection mechanisms …
prevention of and response to outbreaks, evaluation of infection mechanisms …
[HTML][HTML] A sequence-based machine learning model for predicting antigenic distance for H3N2 influenza virus
X Li, Y Li, X Shang, H Kong - Frontiers in Microbiology, 2024 - frontiersin.org
Introduction Seasonal influenza A H3N2 viruses are constantly changing, reducing the
effectiveness of existing vaccines. As a result, the World Health Organization (WHO) needs …
effectiveness of existing vaccines. As a result, the World Health Organization (WHO) needs …
[HTML][HTML] MAIVeSS: streamlined selection of antigenically matched, high-yield viruses for seasonal influenza vaccine production
Vaccines are the main pharmaceutical intervention used against the global public health
threat posed by influenza viruses. Timely selection of optimal seed viruses with matched …
threat posed by influenza viruses. Timely selection of optimal seed viruses with matched …
Neutralization potency of the 2023-24 seasonal influenza vaccine against circulating influenza H3N2 strains
X Huang, Z Cheng, Y Lv, W Li, X Liu… - Human Vaccines & …, 2024 - Taylor & Francis
Seasonal influenza is a severe disease that significantly impacts public health, causing
millions of infections and hundreds of thousands of deaths each year. Seasonal influenza …
millions of infections and hundreds of thousands of deaths each year. Seasonal influenza …
[HTML][HTML] Measuring site-specific glycosylation similarity between influenza a virus variants with statistical certainty
Influenza A virus (IAV) mutates rapidly, resulting in antigenic drift and poor year-to-year
vaccine effectiveness. One challenge in designing effective vaccines is that genetic …
vaccine effectiveness. One challenge in designing effective vaccines is that genetic …
[HTML][HTML] A gradient boosting tree model for multi-department venous thromboembolism risk assessment with imbalanced data
Venous thromboembolism (VTE) is the world's third most common cause of vascular
mortality and a serious complication from multiple departments. Risk assessment of VTE …
mortality and a serious complication from multiple departments. Risk assessment of VTE …
[HTML][HTML] Multi-task learning sparse group lasso: a method for quantifying antigenicity of influenza A (H1N1) virus using mutations and variations in glycosylation of …
Background In addition to causing the pandemic influenza outbreaks of 1918 and 2009,
subtype H1N1 influenza A viruses (IAVs) have caused seasonal epidemics since 1977 …
subtype H1N1 influenza A viruses (IAVs) have caused seasonal epidemics since 1977 …
Sequence-based detection of emerging antigenically novel influenza A viruses
The detection of evolutionary transitions in influenza A (H3N2) viruses' antigenicity is a
major obstacle to effective vaccine design and development. In this study, we describe …
major obstacle to effective vaccine design and development. In this study, we describe …
Adaptive dual graph regularization for clustered multi-task learning
The key challenge of multi-task learning is how to exploit the structure across all tasks. In
practice, relevant tasks are partially associated with similar meaningful feature subgroups …
practice, relevant tasks are partially associated with similar meaningful feature subgroups …