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COVID-19

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Construction of a multi-tissue compound-target interaction network of Qingfei Paidu decoction in COVID-19 treatment based on deep learning and transcriptomic analysis.

Journal of bioinformatics and computational biology
The Qingfei Paidu decoction (QFPDD) is a widely acclaimed therapeutic formula employed nationwide for the clinical management of coronavirus disease 2019 (COVID-19). QFPDD exerts a synergistic therapeutic effect, characterized by its multi-component,...

Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score.

Critical care explorations
BACKGROUND AND OBJECTIVE: To develop the COVid Veteran (COVet) score for clinical deterioration in Veterans hospitalized with COVID-19 and further validate this model in both Veteran and non-Veteran samples. No such score has been derived and validat...

A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data.

JMIR public health and surveillance
BACKGROUND: Multimorbidity is a significant public health concern, characterized by the coexistence and interaction of multiple preexisting medical conditions. This complex condition has been associated with an increased risk of COVID-19. Individuals...

Early detection of cardiorespiratory complications and training monitoring using wearable ECG sensors and CNN.

BMC medical informatics and decision making
This research study demonstrates an efficient scheme for early detection of cardiorespiratory complications in pandemics by Utilizing Wearable Electrocardiogram (ECG) sensors for pattern generation and Convolution Neural Networks (CNN) for decision a...

MGLEP: Multimodal Graph Learning for Modeling Emerging Pandemics with Big Data.

Scientific reports
Accurate forecasting and analysis of emerging pandemics play a crucial role in effective public health management and decision-making. Traditional approaches primarily rely on epidemiological data, overlooking other valuable sources of information th...

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.

Scientific reports
By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with me...

Regularized ensemble learning for prediction and risk factors assessment of students at risk in the post-COVID era.

Scientific reports
The COVID-19 pandemic has had a significant impact on students' academic performance. The effects of the pandemic have varied among students, but some general trends have emerged. One of the primary challenges for students during the pandemic has bee...

Illegal Online Gambling Site Detection using Multiple Resource-Oriented Machine Learning.

Journal of gambling studies
The COVID-19 pandemic has led to faster digitalization and illegal online gambling has become popular. As illegal online gambling brings not only financial threats but also breaches in overall cyber security, this study defines the concept of absolut...

Analyzing pain patterns in the emergency department: Leveraging clinical text deep learning models for real-world insights.

International journal of medical informatics
OBJECTIVE: To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm.

Prediction of COVID-19 patients' participation in financing informal care using machine learning methods: willingness to pay and willingness to accept approaches.

BMC health services research
BACKGROUND: Informal care plays an essential role in managing the COVID-19 pandemic. Expanding health insurance packages that reimburse caregivers' services through cost-sharing policies could increase financial resources. Predicting payers' willingn...