AIMC Topic: COVID-19

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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...

Optimization of vision transformer-based detection of lung diseases from chest X-ray images.

BMC medical informatics and decision making
BACKGROUND: Recent advances in Vision Transformer (ViT)-based deep learning have significantly improved the accuracy of lung disease prediction from chest X-ray images. However, limited research exists on comparing the effectiveness of different opti...

COVID-19 and Pneumonia detection and web deployment from CT scan and X-ray images using deep learning.

PloS one
During the COVID-19 pandemic, pneumonia was the leading cause of respiratory failure and death. In addition to SARS-COV-2, it can be caused by several other bacterial and viral agents. Even today, variants of SARS-COV-2 are endemic and COVID-19 cases...

Prospective Randomized Study on the Use of Robot-Assisted Postoperative Visits.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Robot-assisted visits, as part of telemedicine, can offer doctors the opportunity to take care of patients. Due to the COVID-19 pandemic, there has been an increase in telemedicine. The use of teleconsultations, for example, has found its way into t...

Deepvirusclassifier: a deep learning tool for classifying SARS-CoV-2 based on viral subtypes within the coronaviridae family.

BMC bioinformatics
PURPOSE: In this study, we present DeepVirusClassifier, a tool capable of accurately classifying Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral sequences among other subtypes of the coronaviridae family. This classification is ach...