AIMC Topic: Influenza, Human
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Integrating bioinformatics and machine learning to investigate the mechanisms by which three major respiratory infectious diseases exacerbate heart failure.
Scientific reports
Jul 2, 2025
Heart failure (HF) is a severe cardiovascular disease often worsened by respiratory infections like influenza, COVID-19, and community-acquired pneumonia (CAP). This study aims to uncover the molecular commonalities among these respiratory diseases a...
Language models learn to represent antigenic properties of human influenza A(H3) virus.
Scientific reports
Jul 1, 2025
Given that influenza vaccine effectiveness depends on a good antigenic match between the vaccine and circulating viruses, it is important to assess the antigenic properties of newly emerging variants continuously. With the increasing application of r...
ChatGPT-Assisted Deep Learning Models for Influenza-Like Illness Prediction in Mainland China: Time Series Analysis.
Journal of medical Internet research
Jun 27, 2025
BACKGROUND: Influenza in mainland China results in a large number of outpatient and emergency visits related to influenza-like illness (ILI) annually. While deep learning models show promise for improving influenza forecasting, their technical comple...
Leveraging pre-vaccination antibody titres across multiple influenza H3N2 variants to forecast the post-vaccination response.
EBioMedicine
May 26, 2025
BACKGROUND: Despite decades of research on the influenza virus, we still lack a predictive understanding of how vaccination reshapes each person's antibody response, which impedes efforts to design better vaccines. Models using pre-vaccination antibo...
Constructing a screening model to identify patients at high risk of hospital-acquired influenza on admission to hospital.
Frontiers in public health
Apr 16, 2025
OBJECTIVE: To develop a machine learning (ML)-based admission screening model for hospital-acquired (HA) influenza using routinely available data to support early clinical intervention.
Analyzing the impact of COVID-19 on seasonal infectious disease outbreak detection using hybrid SARIMAX-LSTM model.
Journal of infection and public health
Apr 10, 2025
BACKGROUND: This study estimates the incidence of seasonal infectious diseases, including influenza, norovirus, severe fever with thrombocytopenia syndrome (SFTS), and tsutsugamushi disease, in the Republic of Korea from 2005 to 2023. It also examine...
CT Differentiation and Prognostic Modeling in COVID-19 and Influenza A Pneumonia.
Academic radiology
Mar 3, 2025
RATIONALE AND OBJECTIVES: This study aimed to compare CT features of COVID-19 and Influenza A pneumonia, develop a diagnostic differential model, and explore a prognostic model for lesion resolution.
CEL: A Continual Learning Model for Disease Outbreak Prediction by Leveraging Domain Adaptation via Elastic Weight Consolidation.
Interdisciplinary sciences, computational life sciences
Feb 28, 2025
Continual learning is the ability of a model to learn over time without forgetting previous knowledge. Therefore, adapting new data in dynamic fields like disease outbreak prediction is paramount. Deep neural networks are prone to error due to catast...
Disease diagnostics using machine learning of B cell and T cell receptor sequences.
Science (New York, N.Y.)
Feb 21, 2025
Clinical diagnosis typically incorporates physical examination, patient history, various laboratory tests, and imaging studies but makes limited use of the human immune system's own record of antigen exposures encoded by receptors on B cells and T ce...
A prospective real-time transfer learning approach to estimate influenza hospitalizations with limited data.
Epidemics
Feb 7, 2025
Accurate, real-time forecasts of influenza hospitalizations would facilitate prospective resource allocation and public health preparedness. State-of-the-art machine learning methods are a promising approach to produce such forecasts, but they requir...
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