AIMC Topic: SARS-CoV-2

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Pulmonary diseases accurate recognition using adaptive multiscale feature fusion in chest radiography.

Scientific reports
Pulmonary disease can severely impair respiratory function and be life-threatening. Accurately recognizing pulmonary diseases in chest X-ray images is challenging due to overlapping body structures and the complex anatomy of the chest. We propose an ...

Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods.

Scientific reports
COVID-19 has posed a significant global health challenge, affecting individuals across all age groups. While extensive research has focused on adults, pediatric patients exhibit distinct clinical characteristics that necessitate specialized predictiv...

Effects of a Theory- and Evidence-Based, Motivational Interviewing-Oriented Artificial Intelligence Digital Assistant on Vaccine Attitudes: A Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: Attitude-targeted interventions are important approaches for promoting vaccination. Educational approaches alone cannot effectively cultivate positive vaccine attitudes. Artificial intelligence (AI)-driven chatbots and motivational interv...

LGD_Net: Capsule network with extreme learning machine for classification of lung diseases using CT scans.

PloS one
Lung diseases (LGDs) are related to an extensive range of lung disorders, including pneumonia (PNEUM), lung cancer (LC), tuberculosis (TB), and COVID-19 etc. The diagnosis of LGDs is performed by using different medical imaging such as X-rays, CT sca...

A lightweight hybrid DL model for multi-class chest x-ray classification for pulmonary diseases.

Biomedical physics & engineering express
Pulmonary diseases have become one of the main reasons for people's health decline, impacting millions of people worldwide. Rapid advancement of deep learning has significantly impacted medical image analysis by improving diagnostic accuracy and effi...

Respiratory viral infections: when and where? A scoping review of spatiotemporal methods.

Journal of global health
BACKGROUND: Respiratory viral infections pose a substantial disease burden worldwide. Spatiotemporal techniques help identify transmission patterns of these infections, thereby supporting timely control and prevention efforts. We aimed to synthesise ...

Influencing factors and dynamic changes of COVID-19 vaccine hesitancy in China: From the perspective of machine learning analysis.

Human vaccines & immunotherapeutics
Exploring the influencing factors of COVID-19 vaccine hesitancy and summarizing countermeasures is of great significance for effectively addressing potential public health crises. Based on survey data from China, we employed a Gradient Boosting Decis...

A hybrid deep learning model for sentiment analysis of COVID-19 tweets with class balancing.

Scientific reports
The widespread dissemination of misinformation and the diverse public sentiment observed during the COVID-19 pandemic highlight the necessity for accurate sentiment analysis of social media discourse. This study proposes a hybrid deep learning (DL) m...

COVID-19 risk stratification among older adults: a machine learning approach to identify personal and health-related risk factors.

BMC public health
BACKGROUND: The COVID-19 pandemic highlighted the need to understand factors influencing individuals' risk perceptions and health behaviors. This study aimed to explore the roles of individuals' knowledge, perception, and health-related issues in det...

Differentiation of COVID-19 from other types of viral pneumonia and severity scoring on baseline chest radiographs: Comparison of deep learning with multi-reader evaluation.

PloS one
Chest X-ray (CXR) imaging plays a pivotal role in the diagnosis and prognosis of viral pneumonia. However, distinguishing COVID-19 CXRs from other viral infections remains challenging due to highly similar radiographic features. Most existing deep le...