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Influenza, Human

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A Deep Learning Approach for Predicting Antigenic Variation of Influenza A H3N2.

Computational and mathematical methods in medicine
Modeling antigenic variation in influenza (flu) virus A H3N2 using amino acid sequences is a promising approach for improving the prediction accuracy of immune efficacy of vaccines and increasing the efficiency of vaccine screening. Antigenic drift a...

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...

Feasibility of Radiomics to Differentiate Coronavirus Disease 2019 (COVID-19) from H1N1 Influenza Pneumonia on Chest Computed Tomography: A Proof of Concept.

Iranian journal of medical sciences
BACKGROUND: Chest computed tomography (CT) plays an essential role in diagnosing coronavirus disease 2019 (COVID-19). However, CT findings are often nonspecific among different viral pneumonia conditions. The differentiation between COVID-19 and infl...

Health Promotion, Health Literacy and Vaccine Hesitancy: The Role of Humanoid Robots.

Inquiry : a journal of medical care organization, provision and financing
The use of humanoid robot technologies within global healthcare settings is rapidly evolving; however, the potential of robots in health promotion and health education is not established. The aim of this study was to explore the impact of a social hu...

Classification of COVID-19 and Influenza Patients Using Deep Learning.

Contrast media & molecular imaging
Coronavirus (COVID-19) is a deadly virus that initially starts with flu-like symptoms. COVID-19 emerged in China and quickly spread around the globe, resulting in the coronavirus epidemic of 2019-22. As this virus is very similar to influenza in its ...

Construction of Influenza Early Warning Model Based on Combinatorial Judgment Classifier: A Case Study of Seasonal Influenza in Hong Kong.

Current medical science
OBJECTIVE: The annual influenza epidemic is a heavy burden on the health care system, and has increasingly become a major public health problem in some areas, such as Hong Kong (China). Therefore, based on a variety of machine learning methods, and c...

Virus Detection and Identification in Minutes Using Single-Particle Imaging and Deep Learning.

ACS nano
The increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive diagnostic methods. Here, we present a methodology for virus detection and identi...

Examining the Use of an Artificial Intelligence Model to Diagnose Influenza: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: The global burden of influenza is substantial. It is a major disease that causes annual epidemics and occasionally, pandemics. Given that influenza primarily infects the upper respiratory system, it may be possible to diagnose influenza i...

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.

Journal of medical Internet research
BACKGROUND: In megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious diseases. Existing prediction and early warning models for influenza and other acute respiratory inf...

Development and validation of a hybrid deep learning-machine learning approach for severity assessment of COVID-19 and other pneumonias.

Scientific reports
The Coronavirus Disease 2019 (COVID-19) is transitioning into the endemic phase. Nonetheless, it is crucial to remain mindful that pandemics related to infectious respiratory diseases (IRDs) can emerge unpredictably. Therefore, we aimed to develop an...