AIMC Topic: COVID-19

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Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing.

Journal of racial and ethnic health disparities
PURPOSE: This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language processin...

ISMI-VAE: A deep learning model for classifying disease cells using gene expression and SNV data.

Computers in biology and medicine
Various studies have linked several diseases, including cancer and COVID-19, to single nucleotide variations (SNV). Although single-cell RNA sequencing (scRNA-seq) technology can provide SNV and gene expression data, few studies have integrated and a...

The AI ethics of digital COVID-19 diagnosis and their legal, medical, technological, and operational managerial implications.

Artificial intelligence in medicine
The COVID-19 pandemic has given rise to a broad range of research from fields alongside and beyond the core concerns of infectiology, epidemiology, and immunology. One significant subset of this work centers on machine learning-based approaches to su...

Artificial intelligence and machine learning responses to COVID-19 related inquiries.

Journal of medical engineering & technology
Researchers and scientists can use computational-based models to turn linked data into useful information, aiding in disease diagnosis, examination, and viral containment due to recent artificial intelligence and machine learning breakthroughs. In th...

Sentiment analysis of Indonesian tweets on COVID-19 and COVID-19 vaccinations.

F1000Research
BACKGROUND: Sentiments and opinions regarding COVID-19 and the COVID-19 vaccination on Indonesian-language Twitter are scarcely reported in one comprehensive study, and thus were aimed at our study. We also analyzed fake news and facts, and Twitter e...

Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells.

Nature communications
T cells have the ability to eliminate infected and cancer cells and play an essential role in cancer immunotherapy. T cell activation is elicited by the binding of the T cell receptor (TCR) to epitopes displayed on MHC molecules, and the TCR specific...

Impact of COVID-19 on arthritis with generative AI.

International immunopharmacology
OBJECTIVE: The study aims to examine the effects of the COVID-19 pandemic on the prevalence of arthritis in the US using a specific generative AI tool.

Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators.

Cell metabolism
Cellular senescence underlies many aging-related pathologies, but its heterogeneity poses challenges for studying and targeting senescent cells. We present here a machine learning program senescent cell identification (SenCID), which accurately ident...

Predicting the wicking rate of nitrocellulose membranes from recipe data: a case study using ANN at a membrane manufacturing in South Korea.

Analytical sciences : the international journal of the Japan Society for Analytical Chemistry
Lateral flow assays have been widely used for detecting coronavirus disease 2019 (COVID-19). A lateral flow assay consists of a Nitrocellulose (NC) membrane, which must have a specific lateral flow rate for the proteins to react. The wicking rate is ...

Artificial intelligence in the healthcare sector: comparison of deep learning networks using chest X-ray images.

Frontiers in public health
PURPOSE: Artificial intelligence has led to significant developments in the healthcare sector, as in other sectors and fields. In light of its significance, the present study delves into exploring deep learning, a branch of artificial intelligence.