AIMC Topic: COVID-19

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Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques.

Scientific reports
Predictive models for determining coronavirus disease 2019 (COVID-19) severity have been established; however, the complexity of the interactions among factors limits the use of conventional statistical methods. This study aimed to establish a simple...

Estimating the causal impact of non-pharmaceutical interventions on COVID-19 spread in seven EU countries via machine learning.

Scientific reports
During the COVID-19 pandemic, Non-Pharmaceutical Interventions (NPIs) were imposed all over Europe with the intent to reduce infection spread. However, reports on the effectiveness of those measures across different European countries are inconclusiv...

Subphenotyping prone position responders with machine learning.

Critical care (London, England)
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a heterogeneous condition with varying response to prone positioning. We aimed to identify subphenotypes of ARDS patients undergoing prone positioning using machine learning and assess their a...

Identification and mechanism analysis of biomarkers related to butyrate metabolism in COVID-19 patients.

Annals of medicine
BACKGROUND: Butyrate may inhibit SARS-CoV-2 replication and affect the development of COVID-19. However, there have been no systematic comprehensive analyses of the role of butyrate metabolism-related genes (BMRGs) in COVID-19.

Transformative biomedical devices to overcome biomatrix effects.

Biosensors & bioelectronics
The emergence of high-performance biomedical devices and sensing technologies highlights the technological advancements in the field. Recently during COVID-19 pandemic, biosensors played an important role in medical diagnostics and disease monitoring...

Modifiable risk factors of vaccine hesitancy: insights from a mixed methods multiple population study combining machine learning and thematic analysis during the COVID-19 pandemic.

BMC medicine
BACKGROUND: Vaccine hesitancy, the delay in acceptance or reluctance to vaccinate, ranks among the top threats to global health. Identifying modifiable factors contributing to vaccine hesitancy is crucial for developing targeted interventions to incr...

Application of the LDA model to identify topics in telemedicine conversations on the X social network.

BMC health services research
The evolution experienced by global society, in the post-COVID 19 era, is marked by the quite obligatory use of digital media in many sectors, as is the case for the health sector. Quite frequently, both patients and health professionals use social m...

Hierarchical agent transformer network for COVID-19 infection segmentation.

Biomedical physics & engineering express
Accurate and timely segmentation of COVID-19 infection regions is critical for effective diagnosis and treatment. While convolutional neural networks (CNNs) exhibit strong performance in medical image segmentation, they face challenges in handling co...

Harnessing Computational Strategies to Overcome Challenges in mRNA Vaccines.

Physiology (Bethesda, Md.)
In recent years, the introduction of mRNA vaccines for SARS-CoV2 and respiratory syncytial virus (RSV) has highlighted the success of the mRNA technology platform. Designing mRNA sequences involves multiple components and requires balancing several p...

PM concentration prediction using machine learning algorithms: an approach to virtual monitoring stations.

Scientific reports
One of the most important pollutants is PM, which is particularly important to monitor pollutant levels to keep the pollutant concentration under control. In this research, an attempt has been made to predict the concentrations of PM using four Machi...