AIMC Topic: COVID-19

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Development of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study.

Frontiers in immunology
BACKGROUNDS: During the Coronavirus Disease 2019 (COVID-19) epidemic, the massive spread of the disease has placed an enormous burden on the world's healthcare and economy. The early risk assessment system based on a variety of machine learning (ML) ...

How generative artificial intelligence portrays science: Interviewing ChatGPT from the perspective of different audience segments.

Public understanding of science (Bristol, England)
Generative artificial intelligence in general and ChatGPT in particular have risen in importance. ChatGPT is widely known and used increasingly as an information source for different topics, including science. It is therefore relevant to examine how ...

Machine learning for anxiety and depression profiling and risk assessment in the aftermath of an emergency.

Artificial intelligence in medicine
BACKGROUND & OBJECTIVES: Mental health disorders pose an increasing public health challenge worsened by the COVID-19 pandemic. The pandemic highlighted gaps in preparedness, emphasizing the need for early identification of at-risk groups and targeted...

COVID-19 from symptoms to prediction: A statistical and machine learning approach.

Computers in biology and medicine
During the COVID-19 pandemic, the analysis of patient data has become a cornerstone for developing effective public health strategies. This study leverages a dataset comprising over 10,000 anonymized patient records from various leading medical insti...

Review of machine learning for lipid nanoparticle formulation and process development.

Journal of pharmaceutical sciences
Lipid nanoparticles (LNPs) are a subset of pharmaceutical nanoparticulate formulations designed to encapsulate, stabilize, and deliver nucleic acid cargoes in vivo. Applications for LNPs include new interventions for genetic disorders, novel classes ...

A novel hybrid deep learning IChOA-CNN-LSTM model for modality-enriched and multilingual emotion recognition in social media.

Scientific reports
In the rapidly evolving field of artificial intelligence, the importance of multimodal sentiment analysis has never been more evident, especially amid the ongoing COVID-19 pandemic. Our research addresses the critical need to understand public sentim...

Relationship matters: Using machine learning methods to predict the mental health severity of Chinese college freshmen during the pandemic period.

Journal of affective disorders
BACKGROUND: Pandemics act as stressors and may lead to frequent mental health disorders. College student, especially freshmen, are particularly susceptible to experiencing intense mental stress reactions during a pandemic. We aimed to identify stable...

Identifying Potential Factors Associated With Racial Disparities in COVID-19 Outcomes: Retrospective Cohort Study Using Machine Learning on Real-World Data.

JMIR public health and surveillance
BACKGROUND: Racial disparities in COVID-19 incidence and outcomes have been widely reported. Non-Hispanic Black patients endured worse outcomes disproportionately compared with non-Hispanic White patients, but the epidemiological basis for these obse...

COVID-19 vaccinations and their side effects: a scoping systematic review.

F1000Research
The COVID-19 virus has impacted people worldwide, causing significant changes in their lifestyles. Since the emergence of the epidemic, attempts have begun to prepare a vaccine that can eliminate the virus and restore balance to life in the entire w...

Large-scale deep learning identifies the antiviral potential of PKI-179 and MTI-31 against coronaviruses.

Antiviral research
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to the global pandemic of Coronavirus Disease (2019) (COVID-19), underscoring the urgency for effective antiviral drugs. Despite the development of different vaccination strategies,...