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COVID-19

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Long-term trend prediction of pandemic combining the compartmental and deep learning models.

Scientific reports
Predicting the spread trends of a pandemic is crucial, but long-term prediction remains challenging due to complex relationships among disease spread stages and preventive policies. To address this issue, we propose a novel approach that utilizes dat...

Innovation in public health surveillance for social distancing during the COVID-19 pandemic: A deep learning and object detection based novel approach.

PloS one
The Corona Virus Disease (COVID-19) has a huge impact on all of humanity, and people's disregard for COVID-19 regulations has sped up the disease's spread. Our study uses a state-of-the-art object detection model like YOLOv4 (You Only Look Once, vers...

Investigation of the potential molecular mechanisms of acupuncture in the treatment of long COVID: a bioinformatics approach.

Cellular and molecular biology (Noisy-le-Grand, France)
Long COVID is a poorly understood condition characterized by persistent symptoms following the acute phase of COVID-19, including fatigue, cognitive impairment, and joint pain. Acupuncture, a key component of traditional Chinese medicine treatment, h...

Plasma cell-free RNA signatures of inflammatory syndromes in children.

Proceedings of the National Academy of Sciences of the United States of America
Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and are often misdiagnosed because of a lack of advanced molecular diagnostic tools. In this study, we explored the utility of circul...

A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.

JAMA health forum
IMPORTANCE: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (...

Assessing the Performance of Machine Learning Methods Trained on Public Health Observational Data: A Case Study From COVID-19.

Statistics in medicine
From early in the coronavirus disease 2019 (COVID-19) pandemic, there was interest in using machine learning methods to predict COVID-19 infection status based on vocal audio signals, for example, cough recordings. However, early studies had limitati...

A Joint Classification Method for COVID-19 Lesions Based on Deep Learning and Radiomics.

Tomography (Ann Arbor, Mich.)
Pneumonia caused by novel coronavirus is an acute respiratory infectious disease. Its rapid spread in a short period of time has brought great challenges for global public health. The use of deep learning and radiomics methods can effectively disting...

A Physics-Informed Neural Network approach for compartmental epidemiological models.

PLoS computational biology
Compartmental models provide simple and efficient tools to analyze the relevant transmission processes during an outbreak, to produce short-term forecasts or transmission scenarios, and to assess the impact of vaccination campaigns. However, their ca...

Internal Medicine Year in Review 2023.

Internal medicine (Tokyo, Japan)
The year 2023 marked a significant change for Internal Medicine, as the number of submissions related to the novel coronavirus infection (COVID-19) declined significantly and interest shifted to other disease fields and research areas. Our journal pu...

Harnessing AI for precision tonsillitis diagnosis: a revolutionary approach in endoscopic analysis.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
BACKGROUND: Diagnosing and treating tonsillitis pose no significant challenge for otolaryngologists; however, it can increase the infection risk for healthcare professionals amidst the coronavirus pandemic. In recent years, with the advancement of ar...