AIMC Topic: Influenza, Human

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A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis.

Journal of medical Internet research
BACKGROUND: The seasonal influenza epidemic poses a persistent and severe threat to global public health. Web-based search data are recognized as a valuable source for forecasting influenza or other respiratory tract infection epidemics. Current infl...

Probability-Based Early Warning for Seasonal Influenza in China: Model Development Study.

JMIR medical informatics
BACKGROUND: Seasonal influenza is a major global public health concern, leading to escalated morbidity and mortality rates. Traditional early warning models rely on binary (0/1) classification methods, which issue alerts only when predefined threshol...

Fast identification of influenza using label-free SERS combined with machine learning algorithms clinical nasal swab samples.

Analytical methods : advancing methods and applications
Influenza virus outbreaks, which have become more frequent in recent years, have attracted global attention. Reverse transcription-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA), as the "gold standard" methods for vi...

Integrating bioinformatics and machine learning to investigate the mechanisms by which three major respiratory infectious diseases exacerbate heart failure.

Scientific reports
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
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
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
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
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
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
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.