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COVID-19

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Psychotropic medications: a descriptive study of prescription trends in Tabriz, Iran, 2021-2022.

BMC psychiatry
INTRODUCTION: Mental disorders, such as anxiety and depression, significantly impacted global populations in 2019 and 2020, with COVID-19 causing a surge in prevalence. They affect 13.4% of the people worldwide, and 21% of Iranians have experienced t...

The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.

Molecular biomedicine
Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates the multidimensional role of AI in the pandemic, which arises as a global health crisis, and i...

Stress Monitoring in Pandemic Screening: Insights from GSR Sensor and Machine Learning Analysis.

Biosensors
This study investigates the impact of patient stress on COVID-19 screening. An attempt was made to measure the level of anxiety of individuals undertaking rapid tests for SARS-CoV-2. To this end, a galvanic skin response (GSR) sensor that was connect...

Exploring happiness factors with explainable ensemble learning in a global pandemic.

PloS one
Happiness is a state of contentment, joy, and fulfillment, arising from relationships, accomplishments, and inner peace, leading to well-being and positivity. The greatest happiness principle posits that morality is determined by pleasure, aiming for...

Machine learning identifies remodeling patterns in human lung extracellular matrix.

Acta biomaterialia
Organ function depends on the three-dimensional integrity of the extracellular matrix (ECM). The structure resulting from the location and association of ECM components is a central regulator of cell behavior, but a dearth of matrix-specific analysis...

A prediction approach to COVID-19 time series with LSTM integrated attention mechanism and transfer learning.

BMC medical research methodology
BACKGROUND: The prediction of coronavirus disease in 2019 (COVID-19) in broader regions has been widely researched, but for specific areas such as urban areas the predictive models were rarely studied. It may be inaccurate to apply predictive models ...

Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Helmet-Continuous Positive Airway Pressure (H-CPAP) is a non-invasive respiratory support that is used for the treatment of Acute Respiratory Distress Syndrome (ARDS), a severe medical condition diagnosed when symptoms like ...

Artificial intelligence-driven rational design of ionizable lipids for mRNA delivery.

Nature communications
Lipid nanoparticles (LNPs) have proven effective in mRNA delivery, as evidenced by COVID-19 vaccines. Its key ingredient, ionizable lipids, is traditionally optimized by inefficient and costly experimental screening. This study leverages artificial i...

Artificial intelligence applied to bed regulation in Rio Grande do Norte: Data analysis and application of machine learning on the "RegulaRN Leitos Gerais" platform.

PloS one
Bed regulation within Brazil's National Health System (SUS) plays a crucial role in managing care for patients in need of hospitalization. In Rio Grande do Norte, Brazil, the RegulaRN Leitos Gerais platform was the information system developed to reg...

Fuzzy APPSS: A novel method for quantifying COVID-19 impact in India under triangular spherical fuzzy environment.

Scientific reports
In the current scenario, decision-making models are essential for analyzing real-world problems. To address the dynamic nature of these problems, fuzzy decision-making models have been proposed by various researchers. However, an advanced technique i...